Building Scalable Machine Learning Solutions

4 days ago


Guntur, Andhra Pradesh, India beBeeMachineLearning Full time ₹ 1,50,00,000 - ₹ 2,50,00,000
Machine Learning Operations Engineer

We are seeking a seasoned Machine Learning Operations (ML Ops) professional to leverage their expertise in deploying, monitoring, and scaling machine learning models on cloud platforms.

  • Key Responsibilities:
  • Deploy and manage ML models on cloud platforms using AWS SageMaker, EKS, Lambda, and GCP Vertex AI, GKE, Cloud Functions.
  • Design and maintain CI/CD pipelines for ML workflows using GitHub Actions, Jenkins, and cloud-native tools.
  • Containerize and orchestrate workloads with Docker and Kubernetes, managing infrastructure via Terraform and CloudFormation.
  • Implement model registries, feature stores, and observability using MLflow, Feast, Prometheus, and Grafana.
  • Collaborate with data scientists to operationalize ML models for personalization, recommendations, and NLP.

Requirements:

  • Minimum 2 years of experience in ML Ops and DS.
  • Proficiency in Python, ML frameworks (Scikit-learn, TensorFlow, PyTorch), and data pipelines (Airflow, Spark, SQL).
  • Bonus: experience with real-time ML serving, A/B testing, or media/recommender systems.

Nice-to-Have:

  • Experience with subscription, media, or recommender systems.
  • Knowledge of experiment design and causal inference.
  • Exposure to real-time ML serving (KFServing, Seldon, Ray Serve).

The ideal candidate will have strong technical skills and the ability to collaborate with data scientists. If you are passionate about building scalable and efficient ML solutions, we encourage you to apply.



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