Key Skills: Machine Learning, AWS, AI/ML, Quick 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

📌 AI/ML Developer (Hyderabad)
🏢 Careernet
📍 Hyderabad