Machine Learning Engineer

About the Role

We are seeking a Machine Learning Engineer with one to two years of experience to build and ship models for client systems in Pune. This role is about production ML as much as modelling: you will take a model from a notebook to a served endpoint, and be accountable for how it behaves once real traffic hits it. You will work closely with backend engineers and take a share of independent ownership over the pipelines you build.

Key Responsibilities

• Design, train, and evaluate machine learning models for production use cases
• Build reliable data pipelines for training and inference, including validation and monitoring for data drift
• Package and deploy models as services, working with backend engineers on integration
• Set up experiment tracking and model versioning so results are reproducible
• Monitor deployed models for performance degradation and retrain when needed
• Optimise model inference for latency and cost on cloud infrastructure
• Write clean, tested Python for both training and serving code
• Collaborate with data engineers on the datasets that feed your models
• Document model design decisions, known failure modes, and retraining triggers
• Take part in code review and technical design discussions

Requirements

• Bachelor’s degree in Computer Science, Data Science, or a related field
• 1-2 years of experience building and deploying machine learning models
• Strong Python and hands-on experience with TensorFlow or PyTorch
• Practical experience with the full ML lifecycle: data prep, training, evaluation, deployment, monitoring
• Working SQL skills for building and querying training datasets
• Experience deploying models on a cloud platform, ideally AWS
• Understanding of model evaluation beyond accuracy — precision/recall, calibration, and drift
• Experience with Docker and containerised model serving
• Comfortable reading and debugging someone else’s model pipeline

What We Offer

• Competitive salary benchmarked to market rates in Pune
• Structured progression with a defined skills framework
• Sponsored certifications and a yearly learning budget
• Hybrid working with flexible hours around core collaboration time
• Health insurance for you and your immediate family
• Peer code review and mentoring from senior engineers on every project