• Design and develop next-generation hardware health monitoring and diagnostic frameworks for large GPU clusters (NVL16/NVL72/GB200+ scale).
• Build predictive analytics pipelines leveraging telemetry, power, and thermal data to anticipate hardware degradation and systemic issues.
• Collaborate with silicon, firmware, and datacenter engineers to identify root causes and remediate large-scale hardware anomalies.
• Define system health KPIs (e.g., NIS/RIS, MTBF, failure domain analysis) and integrate them into real-time observability platforms.
• Lead incident triage for high-impact GPU, network, and cooling issues across distributed clusters.
• Drive automation in health management to reduce manual intervention to the top 5% of anomalies.
• Partner with cross-functional teams to influence hardware design for reliability, thermal efficiency, and serviceability.

Required Qualifications: 

• Bachelor’s Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
  • OR equivalent experience.

Preferred Qualifications: 

Software Engineering IC5 – The typical base pay range for this role across the U.S. is USD $142,800 – $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 – $304,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

Software Engineering IC6 – The typical base pay range for this role across the U.S. is USD $165,600 – $296,400 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $220,800 – $331,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Microsoft AI Health

Help Build the Future of AI in Healthcare

Microsoft AI is building frontier AI products and platforms designed to transform how people experience healthcare. We are creating new capabilities that can improve access, support clinicians, empower patients, and unlock new models of care across the healthcare ecosystem. 

We are looking for an exceptional builder to help bring these innovations to market.
This role sits at the center of product strategy, healthcare ecosystem development, commercialization, partnerships, reimbursement, policy, and go-to-market execution. You will help shape how Microsoft AI Health turns breakthrough technology into real-world healthcare impact.
You will not be joining a mature business with a fixed playbook.

You will help create the playbook.

This is a rare opportunity for someone who thrives in ambiguity, thinks from first principles, and wants to help define what becomes possible when frontier AI meets healthcare.

The Opportunity

This is not a traditional partnerships role.
It is a full-stack builder role for someone who can move fluidly across strategy, product, partnerships, commercialization, and execution.
You will help answer some of the most important questions in AI and healthcare:

• What new healthcare experiences become possible with frontier AI?
• How should AI-powered healthcare products reach patients, providers, payers, and health systems?
• Which partnerships can accelerate adoption and deepen product impact?
• What business models and reimbursement pathways will support scalable growth?
• How do we turn early product-market signals into durable, repeatable go-to-market motions?

The right person will bring the structured thinking of a strategist, the ownership mindset of an operator, the curiosity of a product builder, and the adaptability of someone who has built in startup-like environments.

What You’ll Do

Build and Commercialize New Healthcare Products

Help shape early-stage AI healthcare products from concept through market adoption. You will work across product, engineering, research, business development, policy, and commercial teams to define what should be built, how it should be positioned, and how it should scale.

Shape Go-To-Market Strategy

Develop commercialization strategies for new healthcare offerings, including product-market fit, customer segmentation, distribution, pricing, growth strategy, and sales enablement. You will help determine how Microsoft AI Health brings products to market in a way that is thoughtful, credible, and scalable.

Build Strategic Partnerships

Identify, develop, and execute partnerships across the healthcare ecosystem, including providers, payers, telehealth organizations, digital health companies, health systems, and other key industry stakeholders. You will help determine which partnerships are essential to product value, market adoption, and long-term impact.

Influence Product Direction

Bring market, customer, partner, and ecosystem insight directly into product strategy. You will help translate healthcare needs into product opportunities and ensure we are building solutions that matter to real users.

Shape Ecosystem and Reimbursement Strategy

Partner with government affairs, policy, legal, and reimbursement stakeholders to understand and influence the conditions required for scalable adoption. This may include exploring Medicare, Medicaid, commercial payer, employer, and enterprise pathways.

Create Leverage Across Microsoft

Work with existing Microsoft commercial teams, including MCAPS and other go-to-market partners, to determine when to build dedicated motions and when to enable broader Microsoft channels.

Who You Are

You are a builder at heart.
You are energized by ambiguous problems, emerging markets, and the opportunity to create something new. You are comfortable moving from a high-level strategy conversation to a detailed product or partnership decision. You can work with executives, product leaders, engineers, policy experts, and external partners, while maintaining clarity, urgency, and ownership.
You do not need every answer upfront. You know how to form hypotheses, test them quickly, learn from evidence, and iterate.
You are low ego, high ownership, deeply curious, and mission-driven. You care about building products and businesses that can meaningfully improve people’s lives.

What Great Looks Like

The strongest candidates will demonstrate:

Entrepreneurial Ownership

You take responsibility end to end. You do not wait for perfect structure, perfect information, or permission to move important work forward.

Strategic Rigor

You bring clear thinking to ambiguous problems. You can separate signal from noise, develop hypotheses, evaluate tradeoffs, and make strong recommendations.

Healthcare Fluency

You understand the complexity of the U.S. healthcare ecosystem, including providers, payers, reimbursement, health systems, digital health, policy, and commercial adoption.

Commercial Instinct

You understand how products become businesses. You can identify market opportunities, define growth motions, evaluate business models, and create paths to scale.

Product Orientation

You think deeply about users, customer needs, product value, and adoption. You can influence product decisions without needing to formally own the product roadmap.

Partnership Judgment

You know how to identify the right partners, structure meaningful collaborations, and build relationships that create durable value.

Adaptability

You are comfortable operating like a “stem cell” talent, able to flex across disciplines and specialize as the business evolves.

Clear Communication

You simplify complexity. You communicate with precision. You create alignment across senior stakeholders and cross-functional teams.

MAI Culture Alignment

Microsoft AI is building with a high bar for talent, speed, rigor, and impact. The people who thrive here are deeply mission-driven, intellectually honest, low ego, and energized by doing the best work of their lives.
This role requires someone who embodies that culture.
We are looking for someone who:

• Raises the talent density of every team they join
• Operates with urgency without sacrificing long-term judgment
• Takes ownership through completion
• Uses evidence, customer insight, and clear reasoning to guide decisions
• Asks hard questions and updates their thinking quickly
• Simplifies complexity rather than adding process
• Works as a genuine team player with low ego
• Communicates clearly, directly, and thoughtfully
• Builds for users, not internal convenience
• Thrives in small, high-impact teams with minimal hierarchy

This is a role for someone who wants to help build, learn, iterate, and create impact at the frontier of AI and healthcare.

Ideal Background

We are less focused on titles and more focused on pattern recognition.
Strong candidates may bring a combination of:

• Top-tier strategy consulting experience in healthcare
• Operating experience in healthcare technology, digital health, AI, life sciences, payer, provider, or healthcare services
• Startup or high-growth company experience
• Product commercialization experience
• Strategic partnerships or business development experience
• New venture creation, incubation, or zero-to-one building experience
• Experience working across policy, reimbursement, and healthcare commercialization

Relevant backgrounds may include candidates from firms such as McKinsey, Bain, BCG, LEK, Oliver Wyman, Accenture Strategy, or other high-caliber healthcare strategy environments, particularly those who have moved into operating roles and helped build products, businesses, partnerships, or growth engines.

Why This Role Matters

Most healthcare roles optimize existing systems.
Most AI roles focus on building technology.
This role is about connecting the two.
You will help translate frontier AI into healthcare products, partnerships, business models, and go-to-market strategies that can create real-world impact. You will work on problems where the answers are not obvious yet, but where the opportunity is enormous.
For the right person, this is more than a partnerships role.
It is a chance to help define the future of AI in healthcare, from the ground up.

Required/minimum qualifications

• Bachelor’s Degree in Business, Liberal Arts, Sciences, or related field AND 12+ years relevant work experience in a relevant role in healthcare (e.g. healthcare startup, consulting, venture capital, business development, or related field) OR equivalent experience.

Additional or preferred qualifications

• Deep knowledge of the US healthcare market
• Exceptional ability to develop and build trusting relationships with executive-level partners
• Strong communication, presentation and project management skills
• Ability to produce high quality written and presentation materials (PowerPoint, Word) with excellent attention to detail
• Strong numerical analysis (Excel) and financial literacy (understand fundamentals of P&L, balance sheet etc)
• Drive and initiative to maintain momentum, even when working solo
• Work at high speed with autonomy in a rapidly changing environment
• Relish ambiguity/uncertainty

Business Development IC5 – The typical base pay range for this role across the U.S. is USD $130,900 – $251,900 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $165,600 – $272,300 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

Business Development IC6 – The typical base pay range for this role across the U.S. is USD $155,800 – $277,200 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $202,400 – $303,600 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Our team is led by Mustafa Suleyman, CEO of Microsoft AI. We bring together leading researchers, engineers, and product builders who have contributed to many of the most significant advances in modern AI.

As a Principal Product Manager, you will help shape the next generation of AI models. Working backward from customer and product needs, you will identify opportunities for new research, develop evaluations and datasets, and partner closely with researchers and engineers to drive model development and deployment. You will play a critical role in translating emerging capabilities into impactful products and experiences.

Required/Minimum Qualifications

Product Management IC5 – The typical base pay range for this role across the U.S. is USD $142,800 – $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 – $304,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

Product Management IC6 – The typical base pay range for this role across the U.S. is USD $165,600 – $296,400 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $220,800 – $331,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Build AI Data Infrastructure and Data Engines
Develop and evolve large-scale AI data infrastructure for frontier AI lab. Own data collection, ingestion, cleaning, curation, generation, governance, metadata management, query , analytic and hybrid search , building reusable, observable, and explainable EB-scale data platform that support high-quality data for pre-training and post-training workloads.

Develop Intelligent Multimodal Data Processing Systems
Lead automated understanding and processing of text, images, video, documents. Build labeling and taxonomy systems, semantic feature extraction, data quality modeling, and automated data governance capabilities. Design and train models for classification, recognition, captioning, quality scoring, prediction, and related data-processing tasks.

Build AI-Native Data Pipelines
Leverage LLMs, VLMs, and Agents to build intelligent data pipelines that automate data collection, filtering, deduplication, quality diagnosis, annotation/re-labeling, generation, scheduling, orchestration, and anomaly detection. Use AI-native workflows to significantly reduce manual data operations and improve pipeline scalability and efficiency.

Build AI-Native Data Storage and Table Layers
Design open, AI-optimized storage using Lance, Iceberg, Paimon, and Parquet. Support multimodal
data and embeddings, fast random access and scans, schema evolution, transactions, versioning/
time travel, indexing, and interoperable access across training and query engines.

Discover and Build Rare, High-Value Datasets
Develop differentiated datasets for challenging domains, including web/PDF/encyclopedic/private/query-based text data as well as real-world multimodal scenarios such as retail inspection, warehouse inspection, healthcare, education, OCR, GUI interaction, and multimodal trajectories. Apply a combination of real-world data collection, human annotation, and synthetic data generation to produce rare and high-value datasets.

Drive the Data–Model–Evaluation Iteration Loop
Use evaluation feedback and model failure analysis to identify data gaps and design targeted datasets and synthetic-data strategies. Establish observable metrics that quantify the contribution of data to model capability improvements, continuously update datasets during training, and build an iterative Data → Model → Evaluation → Data optimization loop.

Partner Closely with Model and Training Teams
Collaborate with model researchers and training engineers on training-data construction, data feedback loops, targeted data mining, and evaluation-driven iteration. Use data as a primary lever for improving model capability and become a core driver of AI model training performance.

• Required:
  Master’s Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 3+ years experience in business analytics, data science, software development, data modeling, or data engineering OR Bachelor’s Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+ years experience in business analytics, data science, software development, data modeling, or data engineering OR equivalent experience. 
  Experience with distributed data Platforms such as Spark, Flink or Ray.
  Proficient experience in Python and experience with SQL and Shell. 
  Experience with Multimodal Data (Text, Image, Video, or Audio)
  
  Preferred:
• Hands-on experience building datasets for LLM/VLM/multimodal model pre-training or post-training.
• Experience with synthetic data, including text generation, image-text synthesis, rendering/diffusion-based generation, or multimodal trajectory generation for GUI, search, file-operation, or agentic tasks.
• Familiarity with major evaluation benchmarks such as MMLU, MMBench, MM-BrowseComp, with practical experience using evaluation results and failure analysis to drive targeted data improvements.
• Experience with open file and table formats such as Lance, Iceberg, Paimon and Parquet,including schema evolution, versioning, transactions, indexing, and performance optimization for multimodal AI workloads.
• Solid understanding of LLMs, speech/audio models, vision models, and multimodal models. Hands-on experience with large-scale AI data construction, cleaning, synthesis, or quality evaluation.
• Experience building ETL systems, data models, data pipelines, or data warehouses is strongly preferred. Experience processing large-scale text, image, or video datasets is a plus.
• Familiarity with Agents and modern LLM toolchains, with practical experience—or strong interest—in applying LLMs to data production, analysis, quality control, governance, and pipeline automation.

Data Engineering IC5 – The typical base pay range for this role across the U.S. is USD $142,800 – $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 – $304,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

Data Engineering IC6 – The typical base pay range for this role across the U.S. is USD $165,600 – $296,400 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $220,800 – $331,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

We are looking for a Data Flywheel Infrastructure Engineer to build the infrastructure that continuously turns 1P data, 3P data, model signals, evaluation results, and synthetic data into high-quality training data for frontier LLM and multimodal models.
This role owns the systems connecting:
Data Acquisition → Governance & Compliance → Curation → Training → Evaluation → Failure Mining → Data Improvement
A critical part of the role is enabling aggressive data iteration while ensuring that every dataset is secure, policy-compliant, rights-aware, traceable, and auditable.

1. Build 1P & 3P Data Flywheel Infrastructure
   Build scalable systems for ingesting, processing, curating, versioning, and serving first-party and third-party data for pre-training and post-training. Connect model failures, evaluations, and product signals back into targeted data acquisition, generation, and improvement workflows.
2. Own Data Governance, Security & Compliance Infrastructure
   Build governance and policy enforcement directly into the data platform, including:

• • Data provenance and lineage
  • Usage rights, licensing, and consent metadata
  • PII / sensitive-data detection and protection
  • Access control and data isolation
  • Retention and deletion enforcement
  • Geographic and regulatory restrictions
  • Dataset approval and audit workflows
  • Training eligibility and purpose-based usage controls

1. Build Policy-Aware Data Acquisition & Curation Systems
   Develop automated pipelines for 1P and 3P data ingestion, classification, filtering, deduplication, quality scoring, semantic enrichment, and dataset construction.
   Make governance policies machine-enforceable so that data can automatically be included, excluded, quarantined, or restricted based on its origin, license, sensitivity, consent, geography, and intended model use.
2. Build Evaluation-to-Data Feedback Loops
   Convert model evaluations and real-world failure signals into actionable data tasks through failure clustering, hard-example mining, long-tail discovery, capability-gap detection, and targeted dataset generation.
   Enable rapid iteration from:
   Model Failure → Data Gap → Data Intervention → Training → Evaluation
3. Build Synthetic & AI-Native Data Pipelines
   Use LLMs, VLMs, and Agents to automate data generation, labeling, filtering, quality validation, enrichment, and transformation.
   Maintain clear provenance between human-created, first-party, third-party, model-generated, and derived data, and enforce appropriate policies across each category.
4. Build Data Quality, Attribution & Observability
   Develop metrics and infrastructure to measure dataset quality, coverage, diversity, contamination, duplication, policy compliance, and contribution to model capability improvements.
   Enable researchers to understand which data improves which capabilities and under what governance constraints.

Required

•  Master’s Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 3+ years experience in business analytics, data science, software development, data modeling, or data engineering OR Bachelor’s Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+ years experience in business analytics, data science, software development, data modeling, or data engineering OR equivalent experience.  

•  Software Engineering experience using Python,SQL, Spark/Flink/Ray

Preferred

• Experience building AI training-data governance platforms, including provenance, licensing/rights metadata, consent management, PII handling, policy enforcement, or auditable lineage.
• Experience managing third-party datasets, data partnerships, licensed content, or externally sourced data with complex contractual and usage restrictions.
• Experience building privacy- and security-aware systems for first-party product or user data, including isolation, access controls, retention/deletion, and purpose limitation.
• Experience with data clean rooms, privacy-preserving processing, de-identification, confidential computing, or secure data collaboration.
• Experience building evaluation → failure mining → data generation → training feedback loops.
• Experience with synthetic data, model graders, reward signals, hard-example mining, active learning, or data-mixture optimization.
• Experience with multimodal or agentic datasets including text, image, video, audio, web, GUI, tool-use, or interaction trajectories.
• Understanding of Modern LLM training workflows including Pre-training, SFT, RL/post-training, evaluation, and synthetic data. 
• Strong understanding of data governance, security, privacy, provenance, access control, and data lifecycle management.

Data Engineering IC4 – The typical base pay range for this role across the U.S. is USD $119,800 – $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 – $261,000 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

Data Engineering IC5 – The typical base pay range for this role across the U.S. is USD $142,800 – $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 – $304,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Build 1P & 3P Data Flywheel Infrastructure
Build scalable systems for ingesting, processing, curating, versioning, and serving first-party and third-party data for pre-training and post-training. Connect model failures, evaluations, and product signals back into targeted data acquisition, generation, and improvement workflows.

Own Data Governance, Security & Compliance Infrastructure
Build governance and policy enforcement directly into the data platform, including:

• • Data provenance and lineage
  • Usage rights, licensing, and consent metadata
  • PII / sensitive-data detection and protection
  • Access control and data isolation
  • Retention and deletion enforcement
  • Geographic and regulatory restrictions
  • Dataset approval and audit workflows
  • Training eligibility and purpose-based usage controls

Build Policy-Aware Data Acquisition & Curation Systems
Develop automated pipelines for 1P and 3P data ingestion, classification, filtering, deduplication, quality scoring, semantic enrichment, and dataset construction.
Make governance policies machine-enforceable so that data can automatically be included, excluded, quarantined, or restricted based on its origin, license, sensitivity, consent, geography, and intended model use.

Build Evaluation-to-Data Feedback Loops
Convert model evaluations and real-world failure signals into actionable data tasks through failure clustering, hard-example mining, long-tail discovery, capability-gap detection, and targeted dataset generation.
Enable rapid iteration from:
Model Failure → Data Gap → Data Intervention → Training → Evaluation

Build Synthetic & AI-Native Data Pipelines
Use LLMs, VLMs, and Agents to automate data generation, labeling, filtering, quality validation, enrichment, and transformation.
Maintain clear provenance between human-created, first-party, third-party, model-generated, and derived data, and enforce appropriate policies across each category.

Build Data Quality, Attribution & Observability
Develop metrics and infrastructure to measure dataset quality, coverage, diversity, contamination, duplication, policy compliance, and contribution to model capability improvements.
Enable researchers to understand which data improves which capabilities and under what governance constraints.

Required

• Master’s Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 4+ years experience in business analytics, data science, software development, data modeling, or data engineering OR Bachelor’s Degree in Computer Science, Math, Software Engineering, Computer Engineering, or related field AND 6+ years experience in business analytics, data science, software development, data modeling, or data engineering OR equivalent experience.  
• Software Engineering experience using Python,SQL, Spark/Flink/Ray
  
  Preferred
  
  
• Experience building AI training-data governance platforms, including provenance, licensing/rights metadata, consent management, PII handling, policy enforcement, or auditable lineage.
• Experience managing third-party datasets, data partnerships, licensed content, or externally sourced data with complex contractual and usage restrictions.
• Experience building privacy- and security-aware systems for first-party product or user data, including isolation, access controls, retention/deletion, and purpose limitation.
• Experience with data clean rooms, privacy-preserving processing, de-identification, confidential computing, or secure data collaboration.
• Experience building evaluation → failure mining → data generation → training feedback loops.
• Experience with synthetic data, model graders, reward signals, hard-example mining, active learning, or data-mixture optimization.
• Experience with multimodal or agentic datasets including text, image, video, audio, web, GUI, tool-use, or interaction trajectories.
• Understanding of Modern LLM training workflows including Pre-training, SFT, RL/post-training, evaluation, and synthetic data. 
• Strong understanding of data governance, security, privacy, provenance, access control, and data lifecycle management.

Data Engineering IC5 – The typical base pay range for this role across the U.S. is USD $142,800 – $274,800 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000 – $304,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

Data Engineering IC6 – The typical base pay range for this role across the U.S. is USD $165,600 – $296,400 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $220,800 – $331,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.