AI/ML Developer

Key Skills: Machine Learning, AWS, AI/ML, Fast Api, Generative AI, Python, Tensorflow, Agentic AI, Open AI

Roles and Responsibilities:

• Design, develop, and deploy AI/ML and Generative AI solutions for production environments.
• Build and maintain scalable machine learning pipelines and MLOps workflows.
• Develop REST APIs using FastAPI to serve AI/ML models and applications.
• Train, evaluate, optimize, and deploy machine learning models using TensorFlow, PyTorch, or Keras.
• Develop and integrate LLM-based applications using OpenAI APIs and Agentic AI frameworks.
• Implement CI/CD pipelines for ML model deployment and automate model lifecycle management.
• Deploy AI solutions on cloud platforms such as AWS, Azure, or GCP using containerized environments.
• Collaborate with data engineering and cross-functional teams to integrate AI solutions into enterprise applications.
• Monitor model performance, troubleshoot production issues, and continuously improve AI systems.
• Document technical designs, deployment processes, and best practices.

Skills Required:

• Strong experience in Machine Learning, AI/ML, and Generative AI.
• Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Keras.
• Experience developing APIs using FastAPI.
• Hands-on experience with OpenAI APIs, LLMs, Prompt Engineering, and Agentic AI.
• Experience building and deploying production-grade ML pipelines.
• Strong understanding of MLOps, ML lifecycle, model deployment, and monitoring.
• Experience with MLflow, Kubeflow, AWS SageMaker, Vertex AI, Airflow, Prefect, DVC, or Weights & Biases.
• Knowledge of Docker, Kubernetes, Kafka, Git, and CI/CD tools such as Jenkins.
• Experience working with AWS, Azure, or GCP cloud platforms.
• Understanding of statistical modeling, data mining, and unstructured data analytics.
• Experience integrating AI solutions with data engineering pipelines.

Good to Have:

• Experience with cloud orchestration and infrastructure automation.
• Knowledge of Retrieval-Augmented Generation (RAG), vector databases, and AI agents.
• Familiarity with third-party API integrations and microservices architecture.
• AWS, Azure, or Google Cloud AI/ML certifications.

Education: Bachelor's Degree in related field