Machine Learning Engineer – 2- Bangalore

:-Job Title: Machine Learning Engineer – 2

• Location: Onsite – Bengaluru, Karnataka, India
• Experience Required: 3 – 6 Years
• Compensation: ₹20 – ₹25 LPA
• Employment Type: Full-Time
• Work Mode: Onsite Only (No Remote)
  

About the Company:-

Role Overview:-

Key Responsibilities:-

• Design and develop robust AI product features aligned with user and business needs
• Maintain and enhance existing ML/AI systems
• Build and manage ML pipelines for training, deployment, monitoring, and experimentation
• Deploy scalable inference APIs and conduct A/B testing
• Optimize GPU architectures and fine-tune transformer/LLM models
• Build and deploy LLM applications tailored to real-world use cases
• Implement DevOps/ML Ops best practices with tools like Docker and Kubernetes
  

Tech Stack & Tools

Machine Learning & LLMs

• GPT, LLaMA, Gemini, Claude, Hugging Face Transformers
• PyTorch, TensorFlow, Scikit-learn
  

LLMOps & MLOps

• Langchain, LangGraph, LangFlow, Langfuse
• MLFlow, SageMaker, LlamaIndex, AWS Bedrock, Azure AI
  

Cloud & Infrastructure

• AWS, Azure
• Kubernetes, Docker
  

Databases

• MongoDB, PostgreSQL, Pinecone, ChromaDB
  

Languages

• Python, SQL, JavaScript
  

What You’ll Do

• Collaborate with product, research, and engineering teams to build scalable AI solutions
• Implement advanced NLP and Generative AI models (e.g., RAG, Transformers)
• Monitor and optimize model performance and deployment pipelines
• Build efficient, scalable data and feature pipelines
• Stay updated on industry trends and contribute to internal innovation
• Present key insights and ML solutions to technical and business stakeholders
  

Requirements

Must-Have:-

• 3–6 years of experience in Machine Learning and software/data engineering
• Master’s degree (or equivalent) in ML, AI, or related technical fields
• Strong hands-on experience with Python, PyTorch/TensorFlow, and Scikit-learn
• Familiarity with ML Ops, model deployment, and production pipelines
• Experience working with LLMs and modern NLP techniques
• Ability to work collaboratively in a fast-paced, product-driven environment
• Strong problem-solving and communication skills
  

Bonus

• Certifications such as:
• AWS Machine Learning Specialty
• AWS Solution Architect – Professional
• Azure Solutions Architect Expert
  

Why Apply

• Work directly with a high-caliber founding team
• Help shape the future of AI in the insurance space
• Gain ownership and visibility in a product-focused engineering role
• Opportunity to innovate with state-of-the-art AI/LLM tech
• Be part of a fast-moving team with real market traction
  

📍 Note: This is an onsite-only role based in Bengaluru. Remote work is not available.