Machine Learning Engineer ( Junior)

Key Responsibilities: ● Collaborate with senior ML engineers to design and implement AI product features. ● Train, evaluate, and fine-tune ML and LLM models under guidance. ● Support the development and maintenance of scalable ML pipelines and APIs. ● Assist in data preprocessing, feature engineering, and model evaluation. ● Participate in code reviews, testing, and performance optimization. ● Help deploy and monitor ML models in production environments. ● Learn and apply best practices in LLMOps, DevOps, and cloud deployment. ● Contribute to documentation and internal knowledge-sharing. ● Deploy LLM solutions tailored to specific use cases. ● Ensure DevOps and LLMOps best practices using Kubernetes, Docker, and orchestration frameworks. Technical Requirements: ● LLM & ML: Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, Llama ● LLMOps: MLFlow, Langchain, Langgraph, LangFlow, Langfuse, LlamaIndex, SageMaker, AWS Bedrock, Azure AI ● Databases: MongoDB, PostgreSQL, Pinecone, ChromDB ● Cloud: AWS, Azure ● DevOps: Kubernetes, Docker ● Languages: Python, SQL, JavaScript ● Certifications (Bonus): AWS Professional Solution Architect, AWS Machine Learning Specialty, Azure Solutions Architect Expert What You'll Do: ● Work on real-world Generative AI and NLP applications for the insurance domain. ● Build and deploy LLM-based pipelines using modern frameworks. ● Gain hands-on experience with cloud ML infrastructure. ● Learn how to manage end-to-end ML workflows—from experimentation to deployment. ● Collaborate with cross-functional teams (data, backend, product). ● Contribute to improving model accuracy, reliability, and scalability. What You Need to Succeed: ● Bachelor’s or Master’s degree in Computer Science, Machine Learning, or related field. ● 1–2 years of experience in ML, data science, or related software engineering roles (internships count). ● Strong understanding of ML fundamentals, deep learning architectures, and data processing. ● Experience building or fine-tuning models using Python ML frameworks. ● Curiosity, problem-solving mindset, and eagerness to learn new technologies. ● Ability to work collaboratively in a fast-paced, high-impact environment.

Job Types: Full-time, Permanent

Pay: ₹1,200,000.00 - ₹1,800,000.00 per year

Experience:

• Total work: 1 year (Preferred)
• LLM: 1 year (Preferred)
• NLP: 1 year (Preferred)
• Deep learning: 1 year (Preferred)

Work Location: In person