Remote ML Engineer: LLM SaaS for Impact & Growth

Blue Voice Inc.; San Francisco (CA); Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Remote-friendly

Health benefits

Equity opportunities

Job summary

Blue Voice Inc. is seeking a Machine Learning Engineer to design, implement, and iterate on our core SaaS product.

You will own the ML lifecycle from design to training and evaluation, while also contributing to backend and full-stack initiatives beyond ML scope. The role requires Python expertise, strong ML fundamentals, experience deploying customer-facing SaaS, and collaboration with cross-functional teams.

Qualifications

• Bachelor's degree in CS, Eng or related field.
• 3–4 years of software eng experience; strong shipped work.
• Proficiency in Python and AI integration in dev life cycle.
• Strong ML fundamentals, especially LLMs and related tech.
• Experience developing and deploying customer-facing SaaS apps.
• Backend fundamentals: APIs, data pipelines, testing, debugging.

Responsibilities

• Collaborate with the Director of ML and founding engineering team to design and iterate core SaaS product.
• Handle full ML lifecycle from design to training and evaluation, plus backend work outside ML scope.
• Monitor production quality, surface regressions and triage customer issues end-to-end.
• Stay updated on ML developments, especially LLMs and RAG, and discuss new tools and approaches.
• Participate in product decisions and collaborate across teams (CS, sales).

Skills

Python

LLMs

SaaS

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

APIs

Data pipelines

Testing & debugging

React Native

AWS

CI/CD

Agile

Job description

Blue Voice Inc. is seeking a Machine Learning Engineer to design, implement, and iterate on our core SaaS product.

You will own the ML lifecycle from design to training and evaluation, while also contributing to backend and full-stack initiatives beyond ML scope. The role requires Python expertise, strong ML fundamentals, experience deploying customer-facing SaaS, and collaboration with cross-functional teams.