ML Eng 4 Yrs

About The Opportunity

• Design, implement, and productionize ML models and inference pipelines with reliability, scalability, and observability in mind.
• Develop clean, well-tested Python services for data preprocessing, feature engineering, model training, and inference.
• Containerize models and services using Docker and integrate with cloud-hosted deployment pipelines on AWS.
• Collaborate with data scientists and product teams to translate proofs-of-concept into production-ready systems and APIs.
• Implement MLOps best practices—automated training, model versioning, deployment strategies, monitoring, and alerting.
• Drive performance tuning and optimization for model latency, throughput, and cost across production workloads.
  

Skills & Qualifications

• Python
• PyTorch
• TensorFlow
• Scikit-learn
• SQL
• Docker
• AWS
  

Preferred

• MLflow
• Kubernetes
• Apache Spark
  

Qualifications

• Bachelor's degree in Computer Science, Engineering, Mathematics, or equivalent practical experience.
• Approximately 4 years of hands-on experience in machine learning engineering or related software engineering roles.
• Proven track record deploying ML models to production and maintaining model lifecycle (training, versioning, monitoring).
• Comfort working in remote, cross-functional teams and communicating technical trade-offs to stakeholders.
  

• Fully remote role with flexible working hours and India-based hiring.
• Opportunity to own end-to-end ML features and grow into senior technical roles across product & cloud engineering.
• Learning budget and time for upskilling in MLOps, cloud platforms, and advanced ML techniques.