Senior Machine Learning Engineer (Model Development | MLOps | GenAI)

You are a highly skilled and motivated Senior Machine Learning Engineer with over 5 years of experience in ML model development, MLOps pipelines, Python programming, and hands-on exposure to Generative AI technologies. In this role, you will play a key role in designing, developing, and deploying scalable machine learning models and production-grade AI solutions in a collaborative, fast-paced environment. Your responsibilities will include developing and implementing ML models across various domains such as predictive modeling, NLP, and computer vision. You will also be responsible for building and maintaining end-to-end MLOps pipelines for scalable model training, validation, deployment, and monitoring. Working with GenAI frameworks like LangChain, LlamaIndex, or Hugging Face Transformers for building advanced solutions will be a crucial part of your role. Collaboration with data scientists, data engineers, and DevOps teams to operationalize ML solutions is essential. You will need to write clean, efficient, and well-documented Python code for data preprocessing, feature engineering, and model building. Evaluating model performance, iterative improvements based on experimentation and business feedback, ensuring solutions meet performance, reliability, and scalability requirements, participating in code reviews, sprint planning, and design discussions are all key aspects of this role. To be successful in this position, you should have 5+ years of hands-on experience in Machine Learning and Model Development. Strong proficiency in Python and related ML libraries such as scikit-learn, PyTorch, TensorFlow, Pandas, NumPy is required. Experience with MLOps tools like MLflow, Airflow, Kubeflow, SageMaker, or similar is essential. You should have a solid understanding of Generative AI techniques and experience deploying ML models using containerization (Docker), cloud platforms (AWS/GCP/Azure), and CI/CD workflows. Familiarity with version control (Git), agile methodologies, and collaborative development environments is necessary. Excellent problem-solving, debugging, and analytical skills are crucial for this role. Strong communication and collaboration abilities, comfortable working in a hybrid and globally distributed team, are also required. Nice to have skills include experience with LLMOps and tools like Weights & Biases, VectorDBs (e.g., FAISS, Pinecone, Chroma), a background in software engineering or DevOps, exposure to front-end integration for AI applications (e.g., Streamlit, Gradio), and previous experience working in a late-shift or client-aligned shift model. The shift timings for this role are 2:00 PM to 11:00 PM IST (Hybrid Model 2-3 days onsite per week in Chennai office).,