Machine Learning Research Scientist / Research Engineer, Post-Training
Research novel post-training methods for large language models, focusing on preference optimization, data curation, evaluation, alignment, and robustness across text and multimodal systems. Requires advanced academic training and experience with deep learning, reinforcement learning, and post-training techniques.
About the job
Responsibilities
- Research and develop novel LLM post-training techniques, including supervised fine-tuning (SFT), reinforcement learning from human feedback (RLHF), and reward modeling.
- Optimize data curation and evaluation methods for text and multimodal models.
- Design and experiment with approaches to preference optimization.
- Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness.
- Collaborate with researchers and engineers to define best practices for data-driven AI development.
- Partner with foundation model labs to provide technical and strategic input on generative AI model development.
- Publish research findings in top-tier AI conferences.
Requirements
- Ph.D. or master's degree in Computer Science, Machine Learning, AI, or a related field.
- Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning.
- Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning.
- Published machine learning research in major conferences or journals, such as NeurIPS, ICML, ICLR, ACL, EMNLP, or CVPR.
- Excellent written and verbal communication skills.
Nice-to-haves
- Previous experience in a customer-facing role.
Compensation
- Base salary range: $180,600–$225,750 USD.
- Eligible roles may include equity compensation and benefits such as health, dental, and vision coverage, retirement benefits, a learning and development stipend, generous paid time off, and potentially a commuter stipend.
Skills
LLMs, Supervised Fine-Tuning, RLHF, Reward Modeling, Preference Modeling, Instruction Tuning, Deep Learning, Reinforcement Learning, Model Fine-Tuning, Data Curation, Model Evaluation, Multimodal Models, Python, Machine Learning
Similar jobs
AI Research jobs
Scale AI
San Francisco, CAResearch Scientist focused on evaluating frontier language and multimodal models, diagnosing failure modes, and building rigorous benchmarks. The role requires advanced training in AI or a related field, post-training expertise, and published machine learning research.
Earnin
Mountain View, CA
Build agent-driven chatbots and generative AI workflows for financial-wellness products, owning features from design through impact measurement. The role requires at least three years of software engineering experience, strong system design, maintainable coding practices, and a bachelor’s degree or equivalent experience.
Hightouch
United States
Develops experimental AI techniques and prototypes for agentic marketing applications, with emphasis on image and video generation. The role requires strong backend or probabilistic systems expertise, quantitative thinking, creativity with LLM applications, and product intuition.
Greptile
San Francisco, CA
The Research Engineer will apply advances in agents and language models to build and evaluate multi-agent systems for automated code validation and review. The role requires a computer science or equivalent background, research experience, strong programming skills, and product intuition.
Counsel Health
New York, NYResearch Scientist developing and evaluating health-focused AI models, large language models, and agentic systems for clinical applications. The role requires advanced research experience, strong coding skills, healthcare or clinical-data experience, and top-tier AI/ML publications.