Microsoft is looking to create LLM models for general purpose capabilities and for products, and to push the boundaries of AI toward Humanist Superintelligence—ultra-capable systems that remain controllable, safety-aligned, and anchored to human values.
Requirements
- Coding in languages including, but not limited to, C, C++, C-Sharp, Java, JavaScript, or Python
- Experience in machine learning, software engineering
- Experience with Reinforcement Learning data, fine tuning, or training classifiers or engineering prompts to create SOTA foundation models
- Experience with creating AI that amplifies human potential while ensuring humanity remains firmly in control
- Experience with designing and implementing models for agentive applications
- Experience with building and evaluating large language models
- Experience with software engineering and coding in languages such as C, C++, Java, JavaScript, or Python
Responsibilities
- Own and pursue a research agenda to improve model capability and performance for agentive application.
- Collaborate closely with the other research and product teams, from pretraining to model hosting to unlock new model capabilities.
- Build robust evaluations for tracking modeling improvements.
- Design, implement, test, and debug code across our research stack.
- Develop new methods to train core LLM capabilities (including agentive)
- Collect data, evaluating LLMs, creating data flywheels, tooling for LLM training/evals
- Write production quality code, and creating new user-facing features.
Other
- Bachelor's Degree in Computer Science or related technical field AND 2+ years technical engineering experience
- Master's degree in Computer Science or related technical field AND 1+ years technical engineering experience
- Doctorate in Computer Science, Machine Learning, Human-Centered AI or related field
- Effective communicator and great teammate
- Ability to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location
