AI Summary
Design, implement, and maintain end-to-end ML models and pipelines for production use. Collaborate with product and data teams to translate requirements into performant ML solutions. Contribute to MLOps best practices.
Key Highlights
Design and implement end-to-end ML models and pipelines
Collaborate with product and data teams
Contribute to MLOps best practices
Containerize models and services with Docker and deploy to cloud platforms
Instrument models with monitoring, logging, and automated tests
Technical Skills Required
Benefits & Perks
Fully remote work
Flexible hours
Asynchronous collaboration
Opportunity to work on end-to-end ML product features
Collaborative, learning-oriented engineering culture
Job Description
Machine Learning Engineer
About The Opportunity
A fast-growing player in Enterprise Software Product Engineering and AI/ML solutions, delivering scalable machine-learning features and intelligent automation across cloud-native SaaS platforms. We build production ML systems that power analytics, personalization, and automation for business-critical applications. Remote role based in India.
Role & Responsibilities
- Design, implement, and maintain end-to-end ML models and pipelines for production use—data ingestion, feature engineering, training, validation, and deployment.
- Develop and optimize model code in Python using PyTorch or TensorFlow; ensure reproducibility and robust evaluation.
- Containerize models and services with Docker and deploy to cloud platforms using Kubernetes or managed services.
- Collaborate with product and data teams to translate requirements into performant ML solutions and measurable success metrics.
- Instrument models with monitoring, logging, and automated tests to detect performance drift and maintain SLA targets.
- Contribute to MLOps best practices: CI/CD for models, versioning, experiment tracking, and reproducible pipelines.
Must-Have
- 3 years of hands-on Machine Learning engineering experience (production ML pipelines and deployments).
- Proficiency in Python for ML development and data processing.
- Practical experience with PyTorch or TensorFlow for model development.
- Experience containerizing applications with Docker and deploying on Kubernetes or cloud-managed clusters.
- Working knowledge of AWS services for storage and compute (S3, EC2, EKS/SageMaker) and SQL for data access.
- Strong skills in model validation, A/B testing, monitoring, and troubleshooting model performance in production.
- Experience with MLOps tools such as MLflow, Kubeflow, or CI/CD tooling for ML.
- Background in NLP or Computer Vision projects and familiarity with relevant libraries and pipelines.
- Prior work on scalable feature stores, online inference, or real-time prediction systems.
- Fully remote, India-based role with flexible hours and asynchronous collaboration.
- Opportunity to work on end-to-end ML product features with ownership and visible business impact.
- Collaborative, learning-oriented engineering culture with mentorship and knowledge-sharing.
Skills: llm,python,rag,system desing