Applied Research Engineer

Applied Research Engineer
Location: San Francisco, CA
Compensation: $200,000 – $250,000 + 0.05% – 0.4% Equity
Type: Full-Time
Visa Sponsorship: Not Available
Priority: High (Hiring Multiple)

About the Company

- Client is the only AI research lab exclusively focused on video data.
- The company combines exabyte-scale video infrastructure, novel video understanding techniques, and dozens of data sources to develop high-quality datasets that advance video modeling.
- Video constitutes 80% of internet traffic and is essential for creativity, communication, gaming, AR/VR, and robotics.
- Client has 12 employees and has raised a Series A from Tier 1 investors, including Matrix Partners, Swift Ventures, Y Combinator, and AI Grant.
- The company generates significant revenue and partners with top AI labs, delivering cutting-edge datasets at scale.

About the Role — Applied Research Engineer

As an Applied Research Engineer, you will:

- Build high-performance building blocks and large-scale pipelines to process and understand video data with precision at internet scale.
- Tackle ambiguous research problems, optimize ML models and APIs, and create end-to-end solutions in computer vision, audio, and text processing domains.
- Work with models and APIs, optimizing performance through pre/post-processing, parallelism, pipelining, inference optimization, and occasional fine-tuning.
- This role is ideal for engineers who enjoy both research and production engineering, want to push the frontier of video understanding, and can independently own full pipelines from research to deployment.

Responsibilities

- Develop large-scale video processing pipelines with high precision.
- Optimize ML models and APIs using pre/post-processing, parallelism, pipelining, and inference tuning.
- Collaborate with customers and external teams to define requirements and iterate on solutions.
- Build clean, maintainable code that forms the foundation for research and production systems.
- Contribute to end-to-end products, not just individual models.

Requirements

- Minimum of 4+ years of experience in computer vision or audio processing.
- Strong Python skills and hands-on experience with PyTorch or similar ML frameworks.
- Excellent communication skills, especially with external stakeholders.
- Motivation to work end-to-end on products.
- Ability to break problems down from customer impact to technical building blocks.
- Willingness to work in-person at the San Francisco HQ.

Bonus

- Active contributor to open-source projects.
- Experience as an early hire at a startup.

Green Flags (Strong Matches)

- Research background and ability to work independently on problems.
- Experience at top tech companies or research labs (e.g., Meta, OpenAI, DeepMind, NVIDIA, Waymo, Google).
- Direct experience in computer vision, robotics, or large-scale video/data processing.

Red Flags (Avoid)

- Less than 3 years of relevant experience.
- Lack of independent research or applied work experience.
- No exposure to top-tier tech/research environments.

Ideal Companies

- Meta
- OpenAI
- DeepMind
- NVIDIA
- Waymo
- Google
- Intrinsic
- David AI

Interview Process

1. Pending Approval
2. Application Review
3. Initial Screen
4. Technical Chat with CTO
5. Technical Interview
6. On-site
7. Offer
8. Hired

Benefits & Perks

- Competitive compensation and equity
- Health insurance
- Free lunch and dinner at the office

Biggest Note

- Candidates with similar experience, from top research labs, and graduates from top universities are almost certain to be shortlisted.