Research Engineer

Seldon Technologies, Inc; San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Benefits offered by this job

Visa sponsorship

Relocation support

Health, dental, and vision coverage

Professional development budget

GPU access and Mac machine

Team off-sites and conferences

Transit cost support

Gym membership

Meal stipend

Job summary

Seldon Technologies, Inc. in San Francisco seeks an experienced ML Engineer to turn research prototypes into robust, tested data generation, training, and evaluation pipelines.

You will work alongside researchers to scale post-training systems and develop shared software for growing research. You will build distributed experiments, profile GPU workloads, add tests and experiment tracking, and contribute to tooling that ensures reproducibility as research expands.

Qualifications

• Strong Python programming skills and solid software engineering habits.
• Experience building and debugging software for model training, inference, or data processing.
• An understanding of machine learning experiments and how data, numerical precision, and implementation choices affect results.
• Good software engineering habits, including testing, profiling, version control, and documentation.
• You take initiative and collaborate effectively to solve problems.

Responsibilities

• Turn research prototypes into tested, reusable data generation, training, and evaluation pipelines.
• Build support for distributed experiments, including data loading, checkpointing, and collecting agent interactions.
• Profile workloads and improve GPU utilization, memory use, and data throughput.
• Add tests, experiment tracking, and debugging tools, and ensure engineering changes preserve experimental behavior.

Skills

Python

PyTorch/JAX

ML software development

Experimentation understanding

Testing & profiling

Version control

Documentation

Collaboration

Tools

PyTorch

JAX

Job description

You’ll work alongside researchers to take experimental code beyond the initial prototype. You’ll build, test, and scale post-training pipelines and systems for generating, processing, and evaluating research data. You’ll help shape the implementation from the first experiments and develop shared software that the team can use as the research grows.

What you’ll work on

• Turn research prototypes into tested, reusable data generation, training, and evaluation pipelines.
• Build support for distributed experiments, including data loading, checkpointing, and collecting agent interactions.
• Profile workloads and improve GPU utilization, memory use, and data throughput.
• Add tests, experiment tracking, and debugging tools, and check that engineering changes preserve the intended experimental behavior.

What you’ll bring

• Strong Python skills and experience with PyTorch, JAX, or a similar machine learning framework.
• Experience building and debugging software for model training, inference, or data processing.
• An understanding of machine learning experiments, including how data, numerical precision, and implementation choices can affect results.
• Good software engineering habits, including testing, profiling, version control, and documentation.
• You take initiative and follow through on your work. You’re principled in your decisions, open about uncertainty, and collaborative in how you solve problems.

Nice to have

• Experience with distributed training or data processing using tools such as PyTorch distributed, DeepSpeed, or Ray.
• Familiarity with Hugging Face Transformers, vLLM, or experiment tracking tools such as Weights & Biases and MLflow.
• Experience with reinforcement learning systems or processing video, audio, and image datasets.
• Experience with cloud infrastructure for running machine learning workloads and managing data.
• Comprehensive health, dental, and vision coverage.
• Visa sponsorship and relocation support.
• A professional development budget, the best AI tools, GPUs, a Mac, and the subscriptions you need.
• Team off-sites and conference attendance.
• Support with transportation costs.
• Gym membership and sports club subscriptions to support your wellbeing.
• A food stipend with nearly full meal coverage.