Description

You will own the development, deployment, and scaling of machine learning systems.

This role is on-site.

Responsibilities

• Build and optimize ML pipelines and CI/CD workflows.
• Deploy and scale ML models within cloud environments (GCP, AWS, or Azure).
• Develop solutions leveraging knowledge graphs and vector databases for RAG and semantic search.
• Track and maintain model performance through continuous monitoring.

Required Skills

• 7+ years of experience in ML, AI, or Data Science.
• Strong proficiency in Python, TensorFlow, PyTorch, XGBoost, and SciKit-learn.
• Experience with cloud ML platforms, including Vertex AI.
• Proficiency with infrastructure-as-code tools like Terraform and containerization (Docker, Kubernetes).
• Hands-on experience with MLOps tools such as MLflow.
• Familiarity with big data processing frameworks (Spark, Hive, Hadoop).
• Experience working with vector databases (e.g., Pinecone, Weaviate).

Preferred Skills

• Experience with Azure ML or AWS SageMaker.

Key Skills

Education

Any Gradute