<p><p><b>About the Role :</b></p><p><br/>We are seeking a highly motivated and experienced Machine Learning Engineer to join our AI/ML team in either Mumbai or Bangalore.
The ideal candidate will have hands-on expertise in developing and deploying machine learning models, building generative AI modules like chatbots or conversational agents, and working with modern cloud infrastructure to scale AI solutions.
A solid understanding of microservices architecture is also essential.</p><p><br/>You will play a key role in designing, developing, and deploying intelligent solutions that enhance user experience, automate business workflows, and derive actionable insights from data.</p><p><br/></p><p><b>Key Responsibilities :</b></p><p><br/>- Design, build, and optimize machine learning models for classification, regression, NLP, recommendation systems, and more.<br/><br/></p><p>- Perform data preprocessing, feature engineering, model training, evaluation, and tuning.<br/><br/></p><p>- Work with libraries such as scikit-learn, TensorFlow, PyTorch, Hugging Face, OpenCV, etc.<br/><br/></p><p>- Build or integrate Generative AI modules, including LLM-based chatbots, question-answering systems, language generation, and conversational agents.<br/><br/></p><p>- Fine-tune or utilize models from OpenAI, Anthropic, Google (Gemini), Meta (LLaMA), or open-source LLMs.<br/><br/></p><p>- Leverage frameworks like LangChain, Haystack, or Rasa for building agent workflows and pipelines.<br/><br/></p><p>- Deploy, monitor, and scale ML models and AI workloads using AWS, Azure, or Google Cloud Platform.<br/><br/></p><p>- Utilize services such as SageMaker, Vertex AI, Azure ML Studio, Lambda, Cloud Functions, Docker, and Kubernetes.<br/><br/></p><p>- Set up and manage MLOps pipelines for continuous training and deployment.<br/><br/></p><p>- Develop AI-powered microservices as part of distributed systems.<br/><br/></p><p>- Collaborate with backend teams to expose ML models via REST APIs or gRPC.<br/><br/></p><p>- Ensure robust design, scalability, and fault-tolerance in production systems.<br/><br/></p><p>- Work closely with data scientists, engineers, product managers, and UX teams.<br/><br/></p><p>- Participate in Agile development ceremonies stand-ups, sprint planning, retrospectives.<br/><br/></p><p>- Write clear documentation and share technical insights across Skills & Qualifications Skills :</b></p><p><br/>- Proficiency in Python (NumPy, Pandas, Scikit-learn, FastAPI).<br/><br/></p><p>- Experience with TensorFlow, PyTorch, or other deep learning frameworks.<br/><br/></p><p>- Strong knowledge of NLP, LLMs, transformers, and prompt engineering.<br/><br/></p><p>- Hands-on experience with cloud ML tools (AWS SageMaker, GCP Vertex AI, Azure ML).<br/><br/></p><p>- Familiarity with MLOps tools like MLflow, DVC, Airflow, or Kubeflow.</p><br/></p> (ref:hirist.tech)