Description

You design, develop, and deploy machine learning and deep learning models for enterprise applications, owning the full lifecycle from data pipelines to production monitoring.

This role is on-site.

Responsibilities

• Build and maintain scalable AI-driven microservices and data pipelines using Python.
• Train, evaluate, and tune ML models, optimizing for performance and reliability in production.
• Deploy models using MLOps practices, including CI/CD pipelines and containerized environments.
• Integrate AI solutions into enterprise apps via RESTful APIs and cloud platforms.
• Collaborate with engineering and data teams to translate business requirements into technical AI solutions.

Required Skills

• 12+ years of overall experience in software engineering, AI, or machine learning.
• Strong expertise in Python, including NumPy, Pandas, and FastAPI.
• Hands-on experience with TensorFlow, PyTorch, or Scikit-learn.
• Proven experience deploying and maintaining ML models in production.
• Solid knowledge of AWS, Azure, or GCP.
• Experience with Docker, Kubernetes, and containerized deployments.
• Understanding of MLOps, CI/CD pipelines, and model monitoring.

Preferred Skills

• Experience with NLP, Large Language Models (LLMs), or Generative AI.
• Familiarity with enterprise-scale, distributed systems and data platforms.

Key Skills

Education

Bachelor's degree