Description

You will lead the end-to-end lifecycle of AI/ML projects.

Responsibilities

• Architect and build machine learning pipelines using AWS, Azure, or GCP.
• Drive adoption of MLOps best practices for model versioning, CI/CD, and monitoring.
• Lead ML teams and execute complex AI/ML projects from problem definition through deployment.
• Evaluate and implement advanced techniques in deep learning, NLP, computer vision, and reinforcement learning.
• Mentor junior engineers and manage project timelines and deliverables across cross-functional teams.

Required Skills

• 10+ years of experience in data science or machine learning.
• Master’s or PhD in Computer Science, AI/ML, or Data Science.
• Strong programming proficiency in Python, including TensorFlow, PyTorch, and Scikit-learn.
• Experience with ML pipeline tools such as MLflow, Kubeflow, SageMaker, or Vertex AI.
• Familiarity with big data tools (Spark, Hadoop) and SQL/NoSQL databases.
• Experience architecting solutions on cloud platforms (AWS, Azure, GCP).
• Deep understanding of model interpretability and data governance.

Key Skills

Education

Master’s or PhD in Computer Science, AI/ML, Data Science