ML Product Engineer (Junior)
ML Product Engineer (Junior)
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USD 160000 - 200000
1 Vacancy
Job Description
About Tanagram:
Tanagrams mission is to enable developers to work at the speed of thought. To do that were building a tool that captures hardwon lessons buried in codebases code reviews incident postmortems and Slack chats. We turn those lessons into realtime guardrails that flag or fix risky patterns the moment they reach a pull request and eventually at code generation time so that engineers can ship faster and avoid disaster.
Imagine an ideal staff engineer. They know the entire codebase and how different systems interact. They follow every PR so they know what changes are being made and how patterns evolve. Theyve read all the documentation. They keep uptodate on Slack conversations. Ultimately they index all that information in their heads and deliver impact by showing up everywhere and saying the right things at the right time.
Were building that but at scale for entire teams and companies. Tanagram is an extension of every teams best staff engineer available anywhere and anytime.
About This Role:
As an ML Product Engineer youll leverage the latest ML tools and techniques to enable product functionality including:
Analyzing enterprisescale codebases for implicit dependencies.
Implementing recommendation systems for finding code thats similar to a given pattern.
Extracting patterns from code reviews and documentation.
This role is exploratory we have a good sense of what success looks like but we dont yet know how to get there. You should have a good intuition for the right tools to use and how to configure combine and tweak them to deliver the best results for our users.
Were a small team of generalists and work across multiple domains. Were looking for meticulous highagency people who have good judgment around what problems to solve the skills (or learning ability) to solve it expediently and an understanding of the appropriate quality bar given the surrounding business context.
We will generally work inperson in San Francisco (our office is in Mission Bay) but are open to remote for the right candidate.
Responsibilities:
Research & apply ML algorithms: clustering techniques similarity search entity recognition etc.
Build knowledge graphs from multiple data sources.
Use reasoning models like Qwen2.57BInstruct to refine queries based on existing knowledge.
Help build with the best tools in an AI stack: LLMEvals Guardrails for AI CodeAct (agents writing code to fulfill goals) memory for agents (like Mem0).
What We Offer:
Challenging work on enterprisescale codebases and datasets.
Topofmarket compensation (and a long runway).
Employeefriendly equity terms (low FMV early exercise extended exercise).
Your choice of Macbook Pro computer/office equipment stipend.
Food stipend/reimbursements on meals.
Health dental and vision insurance.
Unlimited PTO.
A relatively unchaotic working environment (we arent pivoting every week).
An opportunity to lead and define our company.
Qualifications:
Experience working with highvolume data in vector databases.
Experience with ML/NLP techniques on production projects.
Selfdirection and outputoriented: you repeatedly independently seek out the most valuable thing you could be doing to achieve scalable results quickly. You do so even when requirements and priorities may be changing rapidly.
Bonus points:
Experience building knowledge graphs and working with graph databases.
If youve previously worked at a startup or founded one yourself.
Compensation:
Depending on the relevance and amount of your experience:
Salary for this position ranges from $160000 to $200000 USD
Equity ranges from 0.5% to 1.5%.
If we move forward with an offer you will have a choice between more cash or more equity.
Required Experience:
Junior IC
Employment Type
Full-Time
