Research Engineer, AI Safety & Alignment
Develops evaluation methods, alignment techniques, and adversarial testing for large language models to ensure safety and alignment with human values. Requires PhD in ML/CS, production code skills, GPU experience, and transformers/RL expertise.
About the job
Responsibilities
- Develop and implement novel evaluation methodologies and metrics to assess the safety and alignment of large language models.
- Research and develop cutting-edge techniques for model alignment, value learning, and interpretability.
- Conduct adversarial testing to proactively uncover potential vulnerabilities and failure modes in our models.
- Analyze and mitigate biases, toxicity, and other harmful behaviors in large language models through techniques like reinforcement learning from human feedback (RLHF) and fine-tuning.
- Collaborate with engineering and product teams to translate safety research into practical, scalable solutions and best practices.
- Stay abreast of the latest advancements in AI safety research and contribute to the academic community through publications and presentations.
Requirements
- Hold a PhD (or equivalent experience) in a relevant field such as Computer Science, Machine Learning, or a related discipline.
- Write clear and clean production-facing and training code.
- Experience working with GPUs (training, serving, debugging).
- Experience with data pipelines and data infrastructure.
- Strong understanding of modern machine learning techniques, particularly transformers and reinforcement learning, with a focus on their safety implications.
- Passionate about the responsible development of AI and dedicated to solving complex safety challenges.
Nice to Have
- Experience with product experimentation and A/B testing.
- Experience training large models in a distributed setting.
- Familiarity with ML deployment and orchestration (Kubernetes, Docker, cloud).
- Experience with explainable AI (XAI) and interpretability techniques.
- Research in AI safety, alignment, ethics, or a related area.
- Knowledge of the broader societal and ethical implications of AI, including policy and governance.
- Publications in relevant academic journals or conferences in the field of machine learning.
Skills
PyTorch, Transformers, Reinforcement Learning, RLHF, Gpus, Data Pipelines, Interpretability, Kubernetes, Docker, Explainable Ai
Similar jobs
AI Research jobs
Baseten
San Francisco, CA
Build and ship agentic AI product experiences, internal automation, and customer-facing features across the stack. The role requires 5+ years of software engineering experience, hands-on experience with AI or LLM-powered products, Python proficiency, and strong autonomy.
Mercor
San Francisco, CA
Leads the design, measurement, publication, and adoption of APEX benchmarks evaluating frontier models on economically valuable professional work. The role requires rigorous research judgment, strong coding and statistical skills, and excellent communication across technical, commercial, and research audiences.
Tessera Labs
San Jose, CA
Research Scientist defining and executing research on reliable long-horizon agents in enterprise environments. The role focuses on post-training and reinforcement learning, agent memory, evaluation, verification, and structured representations, combining hands-on experimentation with product delivery and publication.
The Voleon Group
New York, NYConducts causal inference research for financial market prediction and portfolio optimization, developing and validating models from research through live trading. Requires Ph.D.-level coursework, strong causal inference and statistics expertise, mathematical ability, and production Python skills.
OpenAI
San Francisco, CA
Conduct rigorous people research and applied data science to evaluate talent programs, organizational health, and employee experiences. The role requires advanced expertise in research design, experimentation, measurement, causal inference, statistical modeling, and responsible handling of sensitive employee data.