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2 days ago
We are seeking an experienced Machine Learning Engineer to join our team. Prior to this role, you should have around 2+ years of experience working with ML Ops & DS.
Key Responsibilities and Skills:
- Deploy, monitor, and scale machine learning models on cloud platforms such as AWS (SageMaker, EKS, Lambda) or GCP (Vertex AI, GKE, Cloud Functions).
- Build and maintain continuous integration/continuous deployment pipelines for machine learning workflows using tools like 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 machine learning models for personalization, recommendations, NLP.
- Proficient in Python, machine learning frameworks (Scikit-learn, TensorFlow, PyTorch) and data pipelines (Airflow, Spark, SQL).
- Bonus: experience with real-time machine learning serving, A/B testing, or media/recommender systems.
- Nice-to-Have:
- Experience with subscription, media, or recommender systems.
- Knowledge of experiment design & causal inference.
- Exposure to real-time machine learning serving (KFServing, Seldon, Ray Serve).
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