Description

You will design, develop, and deploy machine learning and deep learning models for real-world business use cases. You own the end-to-end lifecycle from data pipelines to production monitoring.

Responsibilities

• Build and maintain scalable data pipelines and AI-driven microservices using Python.
• Implement model training, evaluation, tuning, and performance optimization techniques.
• Integrate AI/ML solutions into enterprise applications through APIs and cloud platforms.
• Support MLOps practices including CI/CD pipelines, deployment automation, and production monitoring.
• Ensure model reliability, scalability, and performance in production environments.

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 machine learning and deep learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
• Proven experience deploying and maintaining ML models in production environments.
• Strong understanding of cloud platforms such as AWS, Azure, or GCP.
• Experience with Docker, Kubernetes, and containerized deployments.
• Solid knowledge of RESTful APIs and microservices architecture.
• Experience with 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