
ML Model Deployment Specialist
3 days ago
We are seeking a seasoned Machine Learning Engineer to join our team. The ideal candidate will have 2+ years of experience working with ML Ops & DS.
Key Responsibilities:
- Deploy, monitor and scale machine learning models on cloud platforms such as AWS or GCP.
- Design and implement CI/CD 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, or Prometheus/Grafana.
Collaboration with Data Scientists:
- Operationalize machine learning models for personalization, recommendations, NLP.
Technical Requirements:
- Proficient in Python and ML frameworks (Scikit-learn, TensorFlow, PyTorch).
- Familiarity with data pipelines (Airflow, Spark, SQL).
Bonus Experience:
- Real-time ML serving, A/B testing, or media/recommender systems.
Nice-to-Have Experience:
- Subscription, media, or recommender systems.
- Experiment design & causal inference.
- Exposure to real-time ML serving (KFServing, Seldon, Ray Serve).
Education:
- Btech / Mtech degree.
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