AI/ML Developer

Job description

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