Research Intern - AI Safety & Reliability for LLM Systems Job at Microsoft Corporation (Redmond)

Senior Data Scientist - Agentic Systems

The Global Marketing Engines and Experiences (E&E) team within Microsoft is resp...

Location

United States , Redmond

Salary:

119800.00 - 234700.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience

Job Responsibility

AI-Native Operations
Design, build, and ship agentic capabilities that make the analytics team more AI-native, including co-PM agents that triage incoming work, monitor data science workstreams in Azure DevOps, and propose ticket updates that keep our backlog accurate without manual hygiene effort
Build PM-layer agents that read across the Azure Dev Ops (ADO) portfolio to surface risk, estimate effort on new requests, and recommend project plans that managers can adapt rather than write from scratch
Establish shared infrastructure and patterns — prompting, evaluation, orchestration, observability, guardrails — that let the rest of the team build downstream agents reliably
Analyst Delivery Acceleration
Develop LLM-powered internal tools and skills that compress the cycle from analytics request to delivered insight, including capabilities that draft, format, and pressure-test the standard inputs analysts produce for MBR, MMR, and leadership review rhythms
Identify the highest-friction parts of the analyst delivery flow and design generative AI interventions that remove rather than relocate the work
Partner with the analytics team to instrument adoption, measure time saved, and iterate based on real usage rather than projected value
Marketer-Facing Capabilities
Lead the design and delivery of marketer-facing generative AI capabilities, anchored by a conversational analytics agent that allows marketers across Brand, Product Marketing Management (PMM), Customer Insights, and demand generation to self-serve on the analytics questions they bring to the team today

What we offer

Eligible for benefits and other compensation

Fulltime

Software Developer (Artificial Intelligence)

Software Developer (Artificial Intelligence) - Oxford Economics, a leading econo...

Location

United Kingdom

Salary:

Not provided

Oxford Economics

Expiration Date

Until further notice

Requirements

2+ years of professional software engineering experience, shipping production code in modern cloud environments
software engineering fundamentals, clean code, testing, version control, code review, modular design and a feel for when to be pragmatic versus principled
strong proficiency in C#/TypeScript, with comfort working across the stack from APIs through to lightweight user interfaces
experience designing, deploying and operating cloud-native services on Azure and/or AWS, including CI/CD and infrastructure-as-code
demonstrable hands-on experience building with large language models, including prompting, function and tool calling, retrieval-augmented generation, and agent design
practical experience integrating with model APIs (e.g. Anthropic, OpenAI, Azure OpenAI), with a clear understanding of cost, latency, context windows and rate limits
familiarity with vector databases, embeddings and modern retrieval techniques, including semantic search, hybrid search and reranking
knowledge of LLM evaluation: Understand the differences between LLM testing vs traditional software
comfort working across multiple teams and domains, quickly building enough understanding of someone else's problem to develop something useful
a strong bias for shipping prototypes, you would rather get something working in front of users than polish it indefinitely

Job Responsibility

Design, build and ship production software that brings AI capabilities to OE's production teams including agents, retrieval-augmented generation (RAG) pipelines, conversational interfaces, internal tools and client-facing features
embed with delivery teams to understand their domain, identify high-leverage opportunities for AI, and translate them into working software that genuinely improves how they work
collaborate with Product Owners to establish business requirements and develop them into tangible deliverables, adapting based on the business needs
build and operate Model Context Protocol (MCP) servers and other integrations that connect frontier models to OE's data, systems and workflows, including Salesforce, Microsoft 365, Azure and our proprietary economic forecasts and datasets
take ideas from prototype to production end-to-end, owning the full software lifecycle: design, code, testing, CI/CD, observability, cost monitoring, evaluation and safe rollout
apply solid software engineering fundamentals, clean code, testing, modularity, performance, security, to AI-enabled systems, where quality and reliability matter just as much as anywhere else
experiment with new models, frameworks and techniques as they emerge, and form a strong, well-evidenced point of view on what is hype and what is worth betting on
design evaluation harnesses and feedback loops so we can measure whether our features are actually working, and keep improving them as models and data evolve
help shape OE's internal AI tooling, including Claude skills, internal MCP servers, shared libraries and the wider AI application framework
embed AI safety, security and responsible-use practices into everything you build, including data handling, prompt-injection defences, and alignment with ISO 27001 controls and OE's AI Acceptable Use Policy

What we offer

Private Healthcare
Employee Assistance Program
Enhanced Maternity and Paternity Leave
Workplace Nursery Scheme
Cycle to Work Scheme

Fulltime

Senior AI & Data Engineer

The Senior AI & Data Engineer is an individual contributor role that acts as the...

Location

India , Bengaluru

Salary:

Not provided

Hewlett Packard Enterprise

Expiration Date

Until further notice

Requirements

Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, Engineering, Mathematics, or a related technical discipline
PhD is a plus
7 – 10 years of hands-on experience in AI/ML engineering, applied data science, or LLM engineering roles
Proven track record of delivering production AI systems
Deep expertise with at least two major LLM platforms (Claude, GPT, Gemini, or equivalent)
Significant experience with Collibra or an equivalent enterprise data governance platform
Demonstrated experience leading cross-functional AI initiatives and mentoring junior engineers
Strong ML fundamentals alongside modern generative AI skills
Experience with responsible AI practices, including fairness auditing, explainability, and content safety, is strongly preferred

Job Responsibility

Serve as the dual AI & data SME for the team and organization
Define and uphold engineering standards, design patterns, and best practices across both AI and data engineering disciplines
Lead technical discovery for new AI and data use cases
Participate in and lead cross-functional initiatives where AI and data strategy intersect
Mentor and upskill the Applied AI Engineer and AI Data Engineer
Architect and deliver complex agentic AI systems
Design and implement advanced RAG architectures
Lead LLM evaluation frameworks
Assess and implement LLM fine-tuning and alignment strategies
Own LLM integration architecture

What we offer

Health & Wellbeing
Personal & Professional Development
Unconditional Inclusion

Senior Applied Scientist

Core Search and AI team (Bing) is looking for people who want to build the next ...

Location

United States , Redmond

Salary:

119800.00 - 234700.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience
Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience
3+ year of industry experience applying Machine Learning techniques or Data Analysis Applications
Experience building and improving large scale Machine Learning system for search, ads, and recommendation, adopting LLM
Research background on Machine Learning, LLM and NLP
Proficient problem solver: ability to identify and solve problems that the world has not solved before

Job Responsibility

Master one or more subareas and build expertise across a broad research landscape, including advanced research methodologies and applied techniques
Develop deep knowledge of a service, platform, or domain, and identify product opportunities by sharing emerging industry trends and applied technologies
Review business requirements and incorporate research insights to meet strategic goals
Provide direction on the types of data needed to solve complex problems and apply deep subject-matter expertise to drive measurable business impact
Support the onboarding of junior team members and help develop academic collaborators into effective contributors within multidisciplinary teams
Identify promising research talent, engage with the academic community, and strengthen Microsoft’s long-term recruiting pipeline
Document ongoing work, experimental results, and research findings to promote transparency and innovation
Apply understanding of fairness and bias to help shape ethics and privacy policies related to research processes and data collection
Advance LLM post-training and alignment techniques by designing, implementing, and evaluating novel methods that improve reasoning quality, safety, controllability, and factual grounding across large-scale models
Develop next-generation search capabilities by building and optimizing retrieval, ranking, and relevance systems that integrate deeply with LLM-powered experiences

Fulltime

Staff II Software Engineer AI/ML Ops

We're looking for a Lead Data Engineer to design, build, and optimize data pipel...

Location

United States , Pleasanton

Salary:

245000.00 - 307000.00 USD / Year

BlackLine

Expiration Date

Until further notice

Requirements

Strong programming skills in languages such as Python, Java, or Scala
Expertise in ML frameworks (TensorFlow, PyTorch, scikit-learn) and orchestration tools (Airflow, Kubeflow, Vertex AI, MLflow)
Proven experience operating production pipelines for ML and LLM-based systems across cloud ecosystems (GCP, AWS, Azure)
Deep familiarity with LangChain, LangGraph, ADK or similar agentic system runtime management
Strong competencies in CI/CD, IaC, and DevSecOps pipelines integrating testing, compliance, and deployment automation
Hands-on with observability stacks (Prometheus, Grafana, Newrelic) for model and agent performance tracking
Understanding of governance frameworks for Responsible AI, auditability, and cost metering across training and inference workloads
Proficiency in containerization technologies (e.g., Docker, Kubernetes)
Proficient in scripting languages (e.g., Bash, python) for automation
Experience with workflow orchestration tools (e.g., Apache Airflow)

Job Responsibility

Lead data pipeline development: Build and maintain PySpark ETL pipelines with high data quality and performance
Manage integrations: Establish robust connections to client data sources via APIs and tools like FiveTran, Plaid, and BlackLine's own internal connector ecosystem
Ensure reliability: Monitor pipeline performance, automate testing, and validate data accuracy
Optimize for scale: Implement performance improvements (e.g., CDC mechanisms, indexing strategies) for large-scale datasets
Collaborate & innovate: Work with business stakeholders to refine data requirements and integrate cutting-edge AI and big data technologies
Partner with data science, security, and product teams to set evaluation and governance standards (Guardrails, Bias, Drift, Latency SLAs)
Mentor senior engineers and drive design reviews for ML pipelines, model registries, and agentic runtime environments
Lead incident response and reliability strategies for ML/AI systems
Collaborate with development teams to integrate AI solutions into existing workflows and applications
Ensure seamless integration with different platforms and technologies

What we offer

Short-term and long-term incentive programs
Robust offering of benefit and wellness plans

Fulltime

Senior Applied AI Engineer, Image Generation

We’re hiring a Senior Applied AI Engineer, Image Generation to join a fast‑movin...

Location

United States , Redmond

Salary:

119800.00 - 234700.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
Master’s Degree AND 3+ years of experience in engineering, problem solving, model building, evaluation, data analysis OR equivalent experience.
PhD in engineering, applied math, statistics, or related analytical field.
2+ years shipping production-level code, models, or data analysis.
1+ years using AI-assisted coding and analysis techniques.
Solid grasp of deep learning: loss functions, optimization, regularization, training stability
Experience deploying ML models at scale (inference optimization, quantization, distillation)
Familiarity with image preprocessing pipelines, data augmentation, and dataset curation
Experience working on small teams and mid-stage startup environments.
Experience working on AI products.

Job Responsibility

Model Development & Training
Train, fine-tune, and evaluate image generation models (diffusion, GAN, transformer-based)
Implement and adapt techniques from research papers into working production systems
Design and run experiments to improve image quality, diversity, and controllability
Curate, clean, and manage large-scale image-text training datasets
Evaluation, Hillclimbing & Quality Systems
Build and maintain evaluation frameworks for correctness, safety, grounding, and UX quality.
Run hillclimbing loops across prompts, models, and tool‑use strategies to continuously improve assistant performance.
Analyze failure modes, design mitigations, and drive systematic improvements across the stack.
LLM Tooling & Internal Infrastructure

Fulltime

Principal Software Engineer

Are you looking for an opportunity to work with the latest Azure offerings and p...

Location

India , Bangalore

Salary:

Not provided

Microsoft Corporation

Expiration Date

Until further notice

Requirements

10–12+ years of experience in software engineering, with significant experience building scalable backend or distributed systems
Strong programming expertise in one or more languages such as Python, Go, Java, or C#, with experience designing production-grade services and APIs
Experience building AI-powered applications, including integrating LLMs, implementing agent or Copilot workflows, and orchestrating multi-step AI interactions
Hands-on experience with LLM application frameworks and orchestration tools such as Semantic Kernel, LangChain, or similar agent frameworks
Familiarity with retrieval-augmented generation (RAG) architectures, vector databases, embeddings, and semantic search systems
Experience evaluating and improving model performance through prompt design, evaluation frameworks, fine-tuning, or feedback loops
Solid understanding of distributed systems concepts including scalability, reliability, observability, caching, and asynchronous processing
Experience deploying and operating AI workloads in cloud environments (preferably Azure), including containerized services and GPU-enabled infrastructure
Understanding of Responsible AI practices, including model governance, safety, privacy, and evaluation of AI behaviour in production systems
Ability to work across product, research, and engineering teams to translate product scenarios into scalable AI system architectures

Job Responsibility

Design, build, and operate scalable AI systems that power intelligent product experiences, including Copilot and agent-driven workflows
Architect and implement backend services that support multi-step AI interactions, including orchestration pipelines, context management, memory/state persistence, and tool execution
Integrate large language models (LLMs), APIs, and internal services to enable context-aware, human-in-the-loop experiences across customer scenarios
Build and maintain data and inference pipelines that support model training, fine-tuning, evaluation, and real-time inference across diverse data sources
Evaluate, benchmark, and tune AI/ML models (LLMs and traditional models) to meet product requirements for accuracy, latency, reliability, and safety
Implement robust retrieval, grounding, and knowledge integration mechanisms (e.g., RAG systems, semantic indexing, vector search) to power intelligent applications
Collaborate with product managers, software engineers, and researchers to translate product vision into production-ready AI capabilities and measurable outcomes
Ensure reliability, observability, and governance of AI systems, including monitoring model performance, data quality, and responsible AI practices
Build reusable platforms, APIs, and tools that enable teams to rapidly develop AI-powered features and self-service intelligent applications

Fulltime

Principal Research Engineer

As a Principal Research Engineer at Microsoft, you will set the technical vision...

Location

United States , Redmond

Salary:

163000.00 - 296400.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
OR equivalent experience
Ability to meet Microsoft, customer and/or government security screening requirements
Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter

Job Responsibility

Define and execute technical strategy for foundational models, multi-agent systems, and next-generation Copilot experiences, especially within Business & Industry Copilot
Lead cross-team efforts to deliver scalable, reliable, and responsible AI systems
Advance the state of the art and translate breakthroughs into measurable customer and business impact
Architect and deliver complex AI systems across model development, data, infra, evaluation, and deployment spanning multiple product lines
Set technical direction for large programs
drive alignment across Research, Engineering, and Product
Integrate LLMs, multimodal models, multi-agent architectures, and RAG into Microsoft’s ecosystem
Establish best practices for MLOps, governance, and Responsible AI, compliant with Microsoft principles and industry standards
Drive original research and thought leadership (whitepapers, internal notes, patents)
convert insights into shipped capabilities

Fulltime

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Research Intern - AI Safety & Reliability for LLM Systems

Job Description

Job Responsibility

Requirements

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