AI/ML Engineer

Job Title: AI/ML Engineer – Data Science, Generative AI & Computer Vision Experience: 3–6 Years Location: Pune (Chakan & Mundhwa) / Mumbai (Kandivali) Job Overview We are seeking a highly skilled AI/ML Engineer with expertise in Machine Learning, Deep Learning, Computer Vision, NLP, Generative AI, and Large Language Models (LLMs) to design, develop, and deploy production-grade AI solutions.

The ideal candidate will have hands-on experience building scalable AI applications, Retrieval-Augmented Generation (RAG) systems, AI agents, and computer vision models while integrating AI capabilities into enterprise applications using modern MLOps and cloud technologies. This role requires strong problem-solving skills, production-focused development experience, and the ability to collaborate with cross-functional teams to deliver end-to-end AI solutions.

Key Responsibilities

AI/ML & Data Science ● Design, develop, train, evaluate, and deploy Machine Learning and Deep Learning models for production environments. ● Build end-to-end ML pipelines including data collection, preprocessing, feature engineering, model training, validation, deployment, and monitoring. ● Work with structured and unstructured datasets using Python and SQL.

● Optimize model performance through hyperparameter tuning, model evaluation, and continuous monitoring. ● Build scalable AI solutions using FastAPI or Flask. Generative AI & LLMs ● Design and implement production-grade Generative AI applications using Large Language Models (LLMs). ● Build Retrieval-Augmented Generation (RAG) pipelines using embeddings, vector databases, and semantic search.

● Develop AI Agents and multi-agent workflows using frameworks such as: ○ Lang. Chain ○ Lang. Graph ○ Llama. Index ○ Haystack ○ Google ADK ● Implement prompt engineering, context management, model evaluation, and response optimization. ● Integrate AI capabilities into enterprise applications through REST APIs and microservices.

Computer Vision ● Design and deploy Computer Vision solutions for: ○ Image Classification ○ Object Detection (YOLO, Faster R-CNN, SSD) ○ Image Segmentation (U-Net, Mask R-CNN) ○ OCR & Document Understanding ○ Video Analytics ● Fine-tune Deep Learning and Vision Transformer models for production use cases. ● Optimize inference performance using ONNX, TensorRT, or similar optimization frameworks.

Production AI & MLOps ● Deploy AI applications using Docker and Kubernetes. ● Build production-ready APIs using FastAPI or Flask. ● Implement model versioning, monitoring, CI/CD, and lifecycle management using MLflow. ● Work with cloud AI services on AWS, Azure, or GCP (Vertex AI preferred). ● Monitor AI models for performance, drift, observability, and cost optimization.

Collaboration ● Work closely with Data Engineers, Backend Developers, Product Managers, and Business Teams. ● Participate in architecture discussions and AI solution design. ● Research emerging AI technologies and recommend improvements.

Required Skills

● Programming ● Python ● SQL ● Machine Learning ● Deep Learning ● Computer Vision ● Generative AI ● AI Frameworks ● Data Processing ● APIs & Backend ● Databases ● DevOps & MLOps ● Cloud Platforms Good to Have ● Experience with Multi-Agent AI systems ● Claude/OpenAI/Gemini APIs ● Azure OpenAI / AWS Bedrock / Vertex AI ● Databricks ● ONNX ● TensorRT ● Hugging Face ● Document AI ● Manufacturing AI ● Surveillance AI ● Retail AI ● Healthcare AI ● Reinforcement Learning ● Contributions to open-source AI/ML projects ● Cost optimization and AI observability tools Soft Skills ● Excellent analytical and problem-solving abilities.

● Strong communication and stakeholder management skills. ● Self-motivated with a continuous learning mindset. ● Ability to work independently and collaboratively in cross-functional teams. ● Ownership of end-to-end AI solution delivery. ● Production-oriented mindset with focus on scalability, reliability, and business impact.

Preferred Qualifications

● Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or a related field. ● 3–6 years of hands-on experience in AI/ML, Data Science, Computer Vision, NLP, or Generative AI. ● Experience building and deploying enterprise-scale AI solutions in production environments.