Machine Learning Engineer

Machine Learning Engineer
A high-growth, VC-backed SaaS company hiring its founding India team
Location: Remote (India)
About the Company
A venture-backed SaaS company is building out its founding India engineering team and has partnered with Flexiple to hire an early Machine Learning Engineer. You will be one of the first ML hires shaping how the product uses models from the ground up, with direct input into what gets built next. Flexiple is a managed marketplace that helps global companies build high-performing teams and GCCs in India.
Role Overview
As a founding Machine Learning Engineer, you will move fast from prototype to shipped feature, owning models end-to-end in a small, high-ownership team with minimal process overhead.
Key Responsibilities
Rapid Model Shipping
Prototype and ship ML-powered features directly into the product, often within days rather than sprints
Fine-tune and evaluate LLMs or smaller models for the company's specific use case
Make pragmatic build-vs-buy calls between in-house models and third-party APIs
Ownership & Scale
Set up lightweight but solid infrastructure for training, evaluation, and deployment as the product scales
Instrument usage and model performance to guide the next iteration
Work directly with the founders and product team to prioritise what ML should solve next
Ideal Candidate Profile
2 to 6 years in applied machine learning, with at least one product shipped to real users
Comfortable working with ambiguity, thin specs, and fast-changing priorities
Strong Python skills and familiarity with modern LLM and ML tooling
Clear written and spoken English and a reliable remote-work setup
Preferred Qualifications
Experience with LLM fine-tuning, RAG pipelines, or prompt-based systems in production
Prior experience at an early-stage startup or as a founding engineer
A degree in computer science, engineering, or a related field
What We Offer
A founding ML seat with outsized ownership on a fast-moving SaaS product
Remote-friendly, pan-India hiring with long-term placement
Direct, daily collaboration with founders and early product decisions
One application considered for this and future matched roles
Hiring Process
HR Screening → Take-Home Build → Founder Round → Culture Fit

Work arrangement
No