Senior Researcher - AI Agents - Microsoft Research
Indexed description
At MSR AI Frontiers, we pursue ambitious research to advance AI in areas such as modeling, algorithms, agents, and agentic systems. We foster a vibrant environment for multidisciplinary work with an open publication policy, close ties to leading academic institutions, and a commitment to impact beyond research. We regularly release open-source models, libraries, and tools to accelerate community progress, while also working within Microsoft’s ecosystem to ship AI technologies across multiple products, ensuring our innovations create real-world value for people.
We are seeking exceptional candidates to advance the state-of-the-art in agentic systems and ecosystems. Relevant projects from our lab include agentic systems (e.g., Magentic-UI, Magentic-One), ecosystems (e.g., Magentic Marketplace), frameworks (e.g., AutoGen), models (e.g., Phi, Orca) and tools (e.g., AgentInstruct, AutoGen Studio).
Focus areas for this position include, but are not limited to, the following:
- Agentic Systems. Building state-of-the-art agentic systems, applications, and environments.
- Agent Ecosystems. Building agent-native ecosystems (e.g., frontier firms, agentic markets) where agents can effectively collaborate alongside people and other agents.
- Advanced Agentic Capabilities. Post-training models for advanced agentic capabilities, including reinforcement learning, fine-tuning, self-play, and synthetic data generation.
- Human-Agent Interaction. Creating novel human-agent interaction techniques and experiences.
- Evaluation & Tooling. Developing evaluation benchmarks, methods, and tooling for agentic capabilities.
- Responsible AI. Ensuring agents operate safely and responsibly while delivering real value to people.
Responsibilities
- Outcome Driven Innovation- The ability to strategically recognize and address unmet needs in industry or knowledge and to create novel, practical, and effective solutions to these unmet needs. This involves the ability to work backwards in research and development, focusing more heavily on the problem to lead to a solution rather than creating something highly original but lacking in application potential.
- Collaborative Innovation- Knowledge of others' expertise and the ability to involve multiple players (within and outside the organization) in the creation or development of novel products, processes, or research streams.
- Problem Solving- The ability to identify problems and review related information to develop and evaluate options and implement solutions.
- Decision Making- The ability to make decisions in a fast-paced, rapidly changing environment. This includes the ability to define, diagnose, and determine an appropriate resolution, recommendation, or decision while considering alternatives and factors (e.g., resources, costs, tradeoffs).
- Scientific Method- Knowledge of and the ability to use an empirical method of acquiring knowledge. This involves careful observation, applying rigorous skepticism about what is observed, formulating a question or hypothesis, testing the hypothesis through experimentation, drawing conclusions, reporting results, and evaluating the process and retesting the hypothesis.
- Doctorate (or currently pursuing) in Computer Science or related fields
- OR equivalent experience
- Publication record as a lead author or essential contributor at top venues such as: CHI, NeurIPS, UIST, ICML, ICLR, ACL, EMNLP, CVPR, AAAI, ICAPS.
- Doctorate in Computer Science or relevant field AND 2 years related research experience
- OR equivalent experience.
- Hands-on experience working with large foundation models (e.g., OpenAI GPT models, LLAMA etc) and state-of-the-art AI/ML frameworks and toolkits (e.g., Pytorch, Tensorflow, Langchain, AutoGen).
- Demonstrated software engineering experience building and deploying prototypes, applications, or open-source technologies. Providing a link to GitHub profile (if available) and/or code samples, is highly encouraged.
- Hands-on experience evaluating AI models or systems (e.g., running benchmark experiments or user studies, analyzing data).
- Experience working in multi-disciplinary teams along with a team player mindset, characterized by effective communication, collaboration, and feedback skills.
- Reference letters are welcomed, though they are not mandatory. Please include them if available.
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.
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