AI / ML Engineer

ML Engineer – Production LLM Systems

📍 Palo Alto, CA (2–3 days onsite)

🚀 Series A | AI-Powered Data Analytics Platform

 

We’re partnered with a well-funded Series A vendor building an AI-powered data analytics platform used by OpenAI, Meta & Google to make critical financial decisions.

 

This is a production-first ML engineering role. The research foundation already exists - your job is to get models reliably into production, operating at scale, with real customers depending on them every day.

 

If you care more about how models behave in the real world than publishing papers or building one-off demos, this role is the one for you!

 

What you’ll work on: 

• Taking ML and LLM systems from prototype to production and owning them end to end
• Deploying and operating models in AWS / GCP / Azure environments, including hybrid and on-prem setups
• Working with modern LLMs (e.g. ChatGPT, Claude, Gemini) as part of larger ML systems -not prompt-only work
• Building and maintaining production ML pipelines, monitoring performance, reliability, and drift
• Partnering closely with product and engineering to ship features used by high-value enterprise customers
• Operating in a fast-moving environment where models, tools, and assumptions evolve constantly

 

What they’re looking for:

• Strong ML fundamentals and a deep understanding of model behavior, limitations, and trade-offs
• Proven experience deploying ML models into production (this is essential)
• Comfort working with real-world data systems and analytics workflows
• Experience with Python and modern ML frameworks (PyTorch, JAX, etc.)
• Cloud experience (AWS and/or GCP strongly preferred; Azure exposure a plus)
• Backgrounds from both startups or larger tech companies are welcome
• Advanced degrees and publications are valued but not required - impact matters

 

Team & environment

• Small, senior team with high ownership
• This role starts as a pure IC role with room to grow as the team scales
• You’ll work directly with experienced ML leadership and influence core technical decisions
• In-person collaboration is valued (2-3 days/week onsite in Palo Alto)

 

Why this role stands out

• Real ML problems with real production constraints
• No “innovation theater” - what you build gets used
• Well-capitalized with strong runway and growing enterprise customers
• Competitive compensation and meaningful equity

 

If you’re an ML engineer who enjoys shipping, owning, and improving production systems, this is a rare opportunity to do impactful work early in a company’s growth.