Machine Learning Engineer

About the Role

Join a US-headquartered product company as they scale their India engineering hub. You will be part of the core platform team responsible for ML features running in production at scale.

This is an opportunity to work on hardening and extending existing systems within a high-performing remote-friendly environment across India.

Key Responsibilities

• Model Development: Design, train, evaluate, and ship models for ranking, recommendation, or NLP use cases. Run structured experiments and A/B tests to validate impact on product metrics.
• Pipeline & Platform Ownership: Build and maintain reliable training and inference pipelines at scale. Own model deployment, versioning, monitoring, and rollback strategies in production environments.
• Cross-Functional Collaboration: Partner with backend engineers to integrate models into existing services ensuring low-latency performance.

Ideal Candidate Profile

• Experience: 2 to 6 years of experience building and shipping ML models into production systems.
• Tech Stack: Strong Python skills with hands-on expertise in PyTorch or TensorFlow. Proficient across the full lifecycle from data pipelines to deployed, monitored models.
• Languages: Clear written and spoken English required for seamless remote collaboration.

Preferred Qualifications

• Familiarity with MLOps tooling (e.g., MLflow, Airflow, Kubeflow).
• Exposure to large-scale data systems such as Spark, feature stores, or streaming pipelines.
• A degree in computer science, statistics, or a related quantitative field.