Lead AI Engineer
- Salary
- $275K–$350K
- Hiring from
- United States
- Work type
- Hybrid
- Posted
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About Us
Job Description
Hybrid role
Day-to-Day Responsibilities:
Fine-tune AI models for specific use cases to optimize performance and accuracy.
Collaborate closely with the engineering team to integrate AI models into the product.
Evaluate and benchmark models, ensuring they meet our latency and accuracy standards.
Set up and manage infrastructure to support efficient AI model deployment.
Work on model evaluation, benchmarking, and observability to ensure robust performance.
Stay updated with the latest advancements in AI to continually refine our approach.
5 - 10 years of experience in machine learning, applied scientist or adjacent roles fine tuning models at tech companies
Hands-on experience fine-tuning models specifically for coding and code generation use cases
OR
fine-tuned models using execution-based feedback (pass/fail signals from running code or tests)
Experience building Small Language Models (SLMs)
Owned AI architecture and technical direction for a product
Undergrad in CS
Manage latency and setup infrastructure for low-latency, high-accuracy AI model usage
Strong proficiency in TypeScript/Node.js and Python
Experience with fine-tuning techniques like LoRA or distillation
Ability to own systems end-to-end and lead execution
- Building a native design tool where code is the core differentiator.
- Focus on AI features to improve efficiency and accuracy in the platform.
- Experience in research and fine-tuning AI models, plus applied experience.
- Focus on model fine-tuning, evaluation, and infrastructure setup for low latency and high accuracy.
- 5+ years of experience, senior-level engineer with AI focus.
- Strong proficiency in TypeScript, Node, and Python.
- This role reports to the CTO and collaborates closely with the engineering team.
- Salary range: $275k to $350k with some flexibility.
- Hybrid role based in the Bay Area, no visa sponsorship.
- Position to be filled as soon as possible.
- Interview process includes initial screening, technical interviews, and a take-home assignment.
- Lack of fine-tuned, efficient models impacting product experience.
- Need to establish internal AI infrastructure for better control and efficiency.
- Someone who has managed AI model fine-tuning and infrastructure setup.
- Background in applied AI roles, possibly from growth-stage companies or startups.