Research Engineer

Factory is hiring a Research Engineer in San Francisco, United States. Level rates it ; you can apply on Factory.

Level's read on this job

Level rates this role Builds AI ●●●●: the job is building AI systems.
The posting mentions Databricks and AI research among its tools and skills.
Level classes it as a mid-level role.
Factory has 65 other open roles on Level.

AI in this role

Databricks

ai-research

About Factory

Our mission is to create a world where software builds and improves itself.

We build the platform for self-improving software development, helping the world's largest enterprise engineering teams turn their organizations into autonomous software factories. Customers including Nvidia, Blackstone, Royal Bank of Canada (RBC), Palo Alto Networks, Adobe, and T-Mobile run Factory to ship code, review PRs, run tests, and deploy continuously - getting smarter with every cycle.

In 2026, we raised $200M at a $5B valuation, bringing our total funding to over $400M. We are backed by world-class investors and operators including Khosla Ventures, Sequoia, Blackstone, Ali Ghodsi (CEO of Databricks), and Frank Slootman (Former CEO of Snowflake).

About the Role

Factory is seeking innovative Research Engineers to design and integrate advanced AI and ML capabilities that revolutionize productivity and accelerate innovation within software organizations.

What you will do and achieve

Design, develop, and deploy AI-driven agentic systems that enhance Factory’s core AI capabilities, focusing on retrieval systems, code generation evaluation, agentic user experience development, and agent backend architecture.
Collaborate with product and engineering teams to incorporate emerging AI research findings into practical, customer-centric solutions.
Engage in iterative development processes, rapidly prototyping and refining AI functionalities based on real-world feedback to meet the evolving needs of developers and enterprises
Take the initiative in identifying and addressing product stability and scalability challenges, ensuring our platform reliably support large-scale operational demands

Qualifications

2+ years of hands-on experience in AI/ML engineering roles post-acquisition of a Bachelor's or Master's degree in Computer Science, Engineering, AI, or a related technical field.
Demonstrated proficiency with LLMs and a track record of applying AI/ML techniques to solve complex, unstructured problems, ideally within the domain of software engineering or related areas.
Self-motivated and autonomous, with a proven ability to navigate ambiguous research projects from conception to impactful deployment.
Strong communication skills that enable you to articulate technical concepts and strategies clearly at all levels, coupled with a strategic mindset oriented towards innovation.
Experience with data-intensive applications and familiarity with the software development lifecycle are highly desirable, though not mandatory.

This is an in-office position (5 days/week) in San Francisco (walking distance to Caltrain)

How we rate this

Research Engineer at Factory rates 84 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Research Engineer is an open job at Factory.
Level rates this role AI Level 4 of 4: Builds AI.
The role is based in San Francisco, CA.
The job was posted on May 2, 2024.
Seniority: mid.
Applications are handled by Factory. Apply on Factory

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI ResearchDatabricks

Questions you could be asked

Tell me about a research question you investigated. What did you find?
Walk me through how you've used Databricks in your day-to-day work.
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: AI Research and Databricks. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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