Ai Ml Engineer
Summary
Designs, develops and deploys ML, deep-learning and Generative AI/LLM solutions for enterprise systems: RAG pipelines with LangChain/LlamaIndex, OpenAI/Hugging Face model integration, prompt engineering, and MLOps with Docker, CI/CD and Azure/AWS/GCP. Hybrid role (2nd shift) in Bengaluru or Mumbai.
IMMEDIATE JOINERS
Role- AI ML Engineer
Experience- 5+ years
Location - Bangalore & Mumbai
Work Mode - Hybrid
Shift Timings - 2nd Shift
JD:
AI & ML Developer with 68 years of experience in machine learning, deep learning, and Generative AI solutions. The ideal candidate will design, develop, and deploy AI/ML models, including Large Language Model (LLM)-based applications, to solve complex business problems.
This role requires hands-on experience in model development, fine-tuning, deployment, and integration of AI solutions into enterprise systems.
Key Responsibilities
Machine Learning Development
- Design, develop, and deploy ML models for predictive analytics and automation.
- Perform data preprocessing, feature engineering, and model evaluation.
- Implement supervised and unsupervised learning algorithms.
- Optimize model performance and scalability.
Generative AI & LLM Implementation
- Build and deploy LLM-based applications using frameworks such as LangChain or LlamaIndex
- Implement RAG (Retrieval-Augmented Generation) pipelines.
- Integrate models from OpenAI, Hugging Face, or open-source LLMs.
- Develop prompt engineering strategies and optimize response quality.
- Work on embeddings, vector databases, and semantic search implementations.
Deployment & MLOps
- Deploy models using APIs or microservices architecture.
- Containerize applications using Docker.
- Implement CI/CD for ML pipelines.
- Monitor model performance and retrain as required.
- Work with cloud platforms such as Azure/AWS/GCP for AI deployments.
Collaboration & Documentation
- Work closely with data engineers, business analysts, and product teams.
- Translate business use cases into AI-driven solutions.
- Document model design, architecture, and deployment processes.
Technical Skills Required
- Strong proficiency in Python
- Experience with ML libraries (Scikit-learn, TensorFlow, PyTorch)
- Hands-on experience with NLP and LLM concepts
- Experience with vector databases (e.g., FAISS, Pinecone, or similar)
- API development using FastAPI or Flask
- Experience with Git and version control
- Understanding of data structures, algorithms, and statistics
Required Qualifications
- Bachelors/Master’s degree in Computer Science, Data Science, AI, or related field
- 6–8 years of experience in ML/AI development
- Strong analytical and problem-solving skills
- Experience working in Agile/Scrum environments
- Good communication and collaboration skills
Thank you
Aswini V - HR
Skills
- Agile
- AI
- Analytics
- API
- Automation
- AWS
- Azure
- CI/CD
- Cloud
- Data Science
- Deep Learning
- Docker
- Embeddings
- FAISS
- FastAPI
- Feature Engineering
- Fine Tuning
- Flask
- GCP
- Generative AI
- Git
- Hugging Face
- LangChain
- LlamaIndex
- LLM
- Machine Learning
- Microservices
- MLOps
- Model Evaluation
- NLP
- OpenAI
- Pinecone
- Predictive Analytics
- Prompt Engineering
- Python
- PyTorch
- RAG
- scikit-learn
- Scrum
- Semantic Search
- Statistics
- TensorFlow
- Vector Databases
- Version Control
