
Data Science Engineer
1 week ago
Job Overview:
Prior to 2+ years of experience working with Machine Learning Operations & Data Science is essential.
Key Responsibilities:
- Deploy, monitor and scale ML models on cloud platforms such as AWS (SageMaker, EKS, Lambda) or GCP (Vertex AI, GKE, Cloud Functions).
- Build and maintain CI/CD pipelines for ML workflows using GitHub Actions / Jenkins / cloud-native tools.
- Containerize and orchestrate workloads with Docker & Kubernetes; manage infrastructure via Terraform/CloudFormation.
- Implement model registries, feature stores, and observability using MLflow, Feast, Prometheus/Grafana.
- Collaborate with data scientists to operationalize ML models for personalization, recommendations, NLP.
Required Skills:
- Proficient in Python and machine learning frameworks such as Scikit-learn, TensorFlow, PyTorch.
- Experience with data pipelines such as Airflow, Spark, SQL.
Preferred Qualifications:
- Real-time ML serving, A/B testing, or media/recommender systems.
Nice-to-Have:
- Knowledge of experiment design & causal inference.
- Exposure to real-time ML serving (KFServing, Seldon, Ray Serve).
Education:
- Btech /Mtech
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