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Senior ML Engineer
Saris AISenior ML Engineer at Saris AI building reliable ML infrastructure and customer-facing AI features. Collaborating with a growing engineering team to tackle automation problems in the banking industry.
About the role
Key responsibilities & impact- Build and own the ML infrastructure that makes our AI systems reliable and improvable, including eval frameworks, prompt management, and model observability
- Ship customer-facing AI features on a consistent cadence, balancing new capability delivery with foundational infrastructure work
- Define and implement the team's approach to evals, LLM routing, prompt engineering, and model selection
- Build pragmatic standards that improve quality without slowing the team down
- Contribute to ML technical direction by proactively surfacing trade-offs and architectural options, helping the team make informed decisions on where ML is headed.
Requirements
What you’ll need- 4+ years of experience in ML or AI engineering, with a track record of shipping production ML systems
- Strong hands-on expertise with LLMs, prompt engineering, evals, and model routing
- Experience building tooling and systems that have real customer impact
- Pragmatic about tradeoffs: knows when good enough is the right call and avoids over-engineering; would rather ship something useful today than design something perfect next quarter
- Comfortable working with moderate direction in ambiguous environments, you can take a scoped problem, work through it, and deliver a shipped solution
- Builds with the end user in mind; understands how ML decisions impact real customers and prioritizes customer value over technical elegance
- Elevates teammates through code review, pairing, and clear communication about technical decisions.
Benefits
Comp & perks- Competitive compensation with premium benefits and equity package.
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
ML infrastructureAI systemseval frameworksprompt managementmodel observabilityLLMsprompt engineeringmodel routingproduction ML systemstooling
Soft Skills
pragmatic decision-makingcustomer-focusedclear communicationcode reviewcollaborationproblem-solvingadaptabilityteam support