Research Engineer, Pre-training
Develops next-generation large language models through research, experimentation, and engineering on pre-training team. Requires strong Python/PyTorch skills, ML expertise, and MS/PhD in related field.
About the job
Key Responsibilities
- Conduct research and implement solutions in model architecture, algorithms, data processing, and optimizer development
- Independently lead small research projects while collaborating on larger initiatives
- Design, run, and analyze scientific experiments to advance understanding of large language models
- Optimize and scale training infrastructure for efficiency and reliability
- Develop and improve dev tooling to enhance team productivity
- Contribute to the entire stack, from low-level optimizations to high-level model design
Qualifications
- Advanced degree (MS or PhD) in Computer Science, Machine Learning, or related field
- Strong software engineering skills with proven track record of building complex systems
- Expertise in Python and experience with deep learning frameworks (PyTorch preferred)
- Familiarity with large-scale machine learning, particularly language models
- Ability to balance research goals with practical engineering constraints
- Strong problem-solving skills and results-oriented mindset
- Excellent communication skills and collaborative work style
- Care about societal impacts of work
Preferred Experience
- Work on high-performance, large-scale ML systems
- Familiarity with GPUs, Kubernetes, and OS internals
- Experience with language modeling using transformer architectures
- Knowledge of reinforcement learning techniques
- Background in large-scale ETL processes
Sample Projects
- Optimizing throughput of novel attention mechanisms
- Comparing compute efficiency of different Transformer variants
- Preparing large-scale datasets for efficient model consumption
- Scaling distributed training jobs to thousands of GPUs
- Designing fault tolerance strategies for training infrastructure
- Creating interactive visualizations of model internals
Skills
Python, PyTorch, Transformers, Kubernetes, Gpus, Machine Learning, LLMs, Reinforcement Learning, Distributed Training, ETL
Similar jobs
AI Research jobs
Anthropic
San Francisco, CA
Research Engineer building large-scale AI capability evaluations, telemetry, data pipelines, and analysis tools for Anthropic’s Takeoff Intel team. The role requires hands-on large language model experimentation, rapid prototyping, data expertise, and strong research collaboration.
Thinking Machines Lab
San Francisco, CA
Research role focused on improving agentic coding capabilities through reinforcement-learning training, synthetic data, coding environments, reward design, and evaluations. Requires strong Python engineering, scalable distributed-training experience, and a bachelor’s degree or equivalent; research experience and a PhD are preferred.
Thinking Machines Lab
San Francisco, CA
Conduct AI safety research across data curation, post-training, evaluations, synthetic data, and red-teaming to improve model reliability on harmful and dual-use requests. The role requires AI safety experience, Python, deep learning frameworks, and scalable technical research skills.
OpenAI
San Francisco, CA
Researcher or engineer focused on designing, evaluating, and productionizing oversight systems and safety mitigations for autonomous AI agents. The role requires strong systems or security reasoning, threat-modeling ability, and experience building practical evaluations and controls.
OpenAI
San Francisco, CA
Researcher focused on training and evaluating frontier AI agents, mining incidents, and building scalable safety measurement systems. The role requires strong research or ML engineering execution, quantitative judgment, and the ability to own ambiguous projects end to end.