Machine Learning Engineer
Location
Seniority
Tech stacks
Machine Learning Engineer
A US-headquartered product company scaling its India hub
Location: Remote (India)
About the Company
A US-headquartered product company with a large, established customer base is scaling its India engineering hub and has partnered with Flexiple to hire a Machine Learning Engineer for its core platform team. The team owns ML features that already run in production at scale and need an engineer who can extend and harden them. Flexiple is a managed marketplace that helps global companies build high-performing teams and GCCs in India.
Role Overview
As a Machine Learning Engineer, you will build, evaluate, and ship models into the company's production product, working closely with backend and platform engineers to keep inference reliable at scale.
Key Responsibilities
Model Development
- Design, train, and evaluate ML models for ranking, recommendation, or NLP use cases within the product
- Run structured experiments and A/B tests to validate model impact against product metrics
- Iterate on features, labels, and model architecture based on production feedback
Production & Platform
- Build and maintain training and inference pipelines that run reliably at scale
- Own model deployment, versioning, monitoring, and rollback in production
- Partner with backend engineers to integrate models into existing services with low latency
Ideal Candidate Profile
- 2 to 6 years building and shipping ML models into production systems
- Strong Python skills and hands-on experience with PyTorch or TensorFlow
- Comfortable with the full lifecycle from data pipelines to deployed, monitored models
- Clear written and spoken English and a reliable remote-work setup
Preferred Qualifications
- Experience with MLOps tooling such as MLflow, Airflow, or Kubeflow
- Exposure to large-scale data systems (Spark, feature stores, or streaming pipelines)
- A degree in computer science, statistics, or a related quantitative field
What We Offer
- A core ML seat embedded in a US product company's India engineering hub
- Remote-friendly, pan-India hiring with long-term placement
- Direct exposure to production-scale ML systems and senior engineering leadership
- One application considered for this and future matched roles
Hiring Process
HR Screening → Technical Assessment → System Design Round → Culture Fit
About Flexiple
Flexiple Service
How does Flexiple work?
Company culture
Build for happiness, not external benchmarks
Unlike the popular narrative of successful tech startups, we bootstrapped our way. This has meant that we have had to deliver value to our customers from Day 1. Our growth has been a consequence of their love for us. Not just that, it also means that we don't have any external benchmarks of success to constantly adhere to. We build for happiness. This doesn't mean that we aren't ambitious, just that our ambitions don't have to be achieved at the cost of our happiness.
Learn by doing
Delegation is great but can be dangerous when one has no clue what they are delegating. So, each of us enjoys the process of learning new things we initially have ZERO knowledge in! This is done by doing and not just by reading. We accept that we will start by being quite shitty at it. The goal is just to be less shitty each day, till suddenly one day we realize that we are actually quite good at it :)
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