Associate ML Engineer

Job Description

Job Title: Associate ML Engineer (Experienced) – Python & LLMs Location: Valsad Experience: 1–2 year About The Role We are looking for an experienced and hands-on Associate ML Engineer with 1–2 years of industry experience in Python development , Machine Learning , and LLM-based solutions . In this role, you will contribute to designing, building, deploying, and optimizing AI/ML systems —including generative AI applications, embeddings, vector search, and chatbot solutions. You will work across the full lifecycle of AI projects, from data processing to model deployment using FastAPI and database-backed systems. Key Responsibilities Develop and maintain AI/ML models using Python, Scikit-Learn, PyTorch, or TensorFlow. Build LLM-driven applications using GPT, BERT, or Transformer-based models. Develop backend APIs (FastAPI) for deploying AI services. Work with structured and unstructured data: cleaning, preprocessing, feature engineering, and evaluation. Implement vector embeddings, similarity search, and LLM-based retrieval pipelines. Optimize model performance and inference latency. Integrate AI models with databases (MySQL, PostgreSQL, MongoDB, etc.). Collaborate with product, backend, and mobile teams for end-to-end delivery. Monitor, maintain, and retrain production ML models as needed. Key Requirements Strong Python programming skills and clean coding practices. Understanding of Machine Learning and Deep Learning fundamentals . Familiarity with LLMs (GPT, BERT, Transformers) and modern ML frameworks. Experience with FastAPI and database integration (e.g., MySQL). Ability to work with datasets: preprocessing, analysis, and model evaluation. Good debugging, problem-solving, and analytical skills. Passion for generative AI, chatbots, and applied AI solutions . Preferred Skills Understanding of prompt engineering, embeddings, or LLM fine-tuning . Experience with cloud AI platforms (Azure AI, AWS Bedrock, OpenAI API, Hugging Face). Understanding of model deployment, CI/CD, and containerization (Docker). Basic understanding of data pipelines, ETL workflows, or MLOps practices. Knowledge of data visualisation, model deployment, and production AI systems . Education B.Tech / B.E / M.Tech / MCA in Computer Science, AI, Data Science, or related fields . Why Join Us Work on cutting-edge generative AI and LLM projects . Build end-to-end AI solutions with Python, FastAPI, and databases. Fast-growing, innovation-driven, and collaborative environment. Exposure to production-grade deployments and modern AI architecture. Required Skills Initiative/Innovation Cross team support Communication