Machine Learning Engineer

Jack; San Francisco (CA); On-site; USD 190,000 - 240,000; Full time

Benefits offered by this job

Health insurance

Series A funding

Small, high-impact team

Direct collaboration with AI labs

Job summary

Jack in San Francisco is seeking a Member of Technical Staff, Machine Learning to own the full ML lifecycle—from customer problems to production deployment.

You will fine-tune PyTorch vision-language and multimodal models, build robust evaluation pipelines, and maintain end-to-end production ML systems with a small, highly capable team in person.

Qualifications

• Strong Python programming experience for production ML.
• Hands-on experience training, fine-tuning, or deploying DL models with PyTorch.
• Experience designing evaluation pipelines and handling edge cases.
• Ability to own projects end-to-end from requirements to deployment.
• Excellent cross-functional communication.

Responsibilities

• Own model quality for customer-facing video understanding tasks.
• Fine-tune vision-language and multimodal models using PyTorch.
• Design automated evaluation and QA pipelines.
• Build high-precision filtering, ranking, retrieval and labeling systems.
• Develop datasets, benchmarks, and evaluation frameworks.
• Maintain production ML pipelines including preprocessing and inference.

Skills

Python

PyTorch

Production ML

Vision-Language

Multimodal

Evaluation Design

End-to-End Ownership

Communication

Job description

Member of Technical Staff, Machine Learning

This is a unique opportunity to join an AI research lab at the cutting edge of multimodal data and foundation models. If you want to own the entire ML lifecycle—from ambiguous customer problems to hands‑on PyTorch fine‑tuning and deploying production systems—this role puts you at the center of frontier AI development. Your work will directly impact the world’s most advanced models, and you’ll collaborate closely with leading labs shaping the future of AI.

What You Will Do

• Take full ownership of model quality for customer-facing video understanding problems, driving projects from initial requirements through to deployed, production-grade systems.
• Fine-tune vision-language and multimodal foundation models using PyTorch for specialized, high-impact tasks.
• Design and implement automated evaluation and QA pipelines, working with both proprietary and open‑source vision-language models.
• Build high‑precision filtering, ranking, retrieval, and labeling systems over internet-scale video datasets.
• Develop the datasets, benchmarks, and evaluation frameworks that continuously raise the bar for model quality.
• Own and maintain production ML pipelines, including data preprocessing, inference, post‑processing, and quality validation.
• Work in‑person in San Francisco, collaborating daily with a small, high‑caliber team and directly with frontier AI labs to translate ambiguous requirements into scalable, robust systems.

What Is Expected

• You are a strong Python engineer with hands‑on experience building production ML systems.
• You have a track record of training, fine‑tuning, or deploying modern deep learning models, especially with PyTorch and vision‑language or multimodal foundation models.
• You bring excellent intuition for evaluation design, dataset quality, and the practical tradeoffs between precision and recall, and you know how to spot edge cases before they reach production.
• You are comfortable owning projects end‑to‑end, from direct customer interaction to internal pipelines and final deployment.
• You communicate clearly and enjoy working cross‑functionally.
• You are able to work onsite in San Francisco five days a week.
• Bonus if you have direct experience with video, multimodal AI, or large‑scale data curation; a background at an AI lab or high‑scale ML infrastructure team is also a plus.

What Is Offered

• Health insurance.
• Series A funding and stability, with work that ships directly into frontier models.
• A small, high‑impact team where your contributions are visible and immediate.
• Direct collaboration with the world’s leading AI labs on projects that define the state of the art.