
Machine Learning Engineer
2 days ago
Prior experience working with machine learning operations and data science is required. The ideal candidate will have a strong background in deploying, monitoring, and scaling machine learning models on cloud platforms such as AWS or GCP.
- Deploy, monitor, and scale ML models on cloud platforms (AWS or GCP)
- Build and maintain continuous integration/continuous deployment pipelines for ML workflows using GitHub Actions or Jenkins
- Containerize and orchestrate workloads with Docker and Kubernetes; manage infrastructure via Terraform or CloudFormation
- Implement model registries, feature stores, and observability using MLflow, Feast, and Prometheus/Grafana
- Collaborate with data scientists to operationalize ML models for personalization, recommendations, and natural language processing
The following skills and qualifications are required:
- Proficient in Python and machine learning frameworks (Scikit-learn, TensorFlow, PyTorch)
- Experience with data pipelines (Airflow, Spark, SQL)
- Knowledge of experiment design and causal inference
- Exposure to real-time ML serving (KFServing, Seldon, Ray Serve)
- BTech/Mtech degree
The following benefits are available:
- Opportunity to work with cutting-edge technology
- Collaborative and dynamic work environment
- Professional growth and development opportunities
The following information is also relevant:
- Experience with subscription, media, or recommender systems is a plus
- Nice-to-have: knowledge of experiment design and causal inference
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