Ai - Machine Learning/Generative AI Engineer - Python/LLM

4 days ago

Bengaluru, Karnataka, India Integers Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Description
Role : Machine Learning & Generative AI Engineer

Job Location : Bangalore (Hybrid 2-3 days from office)

Experience : 3-7 years

About The Role
We are seeking a highly skilled Machine Learning & Generative AI Engineer to design, build, and deploy advanced ML and GenAI solutions.

This role provides the opportunity to work on cutting-edge AI technologies such as LLM fine-tuning, Transformer architectures, Retrieval-Augmented Generation (RAG), and enterprise-scale ML systems.

The ideal candidate will combine strong technical expertise with innovative thinking to deliver impactful AI solutions aligned with business needs.

Required Skills & Qualifications

  • 3 to 7 years of experience in Machine Learning, Deep Learning, and AI model development
  • Strong proficiency in Python and ML frameworks : PyTorch, TensorFlow, Scikit-Learn, MLflow
  • Expertise in Transformer architectures (BERT, GPT, T5, LLaMA, Falcon, etc.) and attention mechanisms
  • Hands-on experience with Generative AI : LLM fine-tuning (LoRA, QLoRA, PEFT, full model tuning), instruction tuning, and prompt optimization
  • Experience with RAG pipelines embeddings, vector databases (FAISS, Pinecone, Weaviate, Chroma), and retrieval workflows
  • Strong foundation in statistics, probability, and optimization techniques
  • Proficiency with cloud ML platforms (Azure ML / Azure OpenAI, AWS SageMaker / Bedrock, GCP Vertex AI)
  • Familiarity with Big Data & Data Engineering : Spark, Hadoop, Databricks, SQL/NoSQL databases
  • Hands-on experience with CI/CD, MLOps, and automation pipelines (Airflow, Kubeflow, MLflow)
  • Experience with Docker, Kubernetes for scalable ML/LLM deployment

Preferred Qualifications

  • Experience in NLP & Computer Vision (Transformers, BERT/GPT models, YOLO, OpenCV)
  • Knowledge of vector search & embeddings for enterprise-scale GenAI solutions
  • Exposure to multimodal AI (text + image/video/audio) and Edge AI / federated learning
  • Familiarity with RLHF (Reinforcement Learning with Human Feedback) for LLMs
  • Understanding of real-time ML applications and low-latency model serving

Key Responsibilities

  • Design, build, and deploy end-to-end ML pipelines including data preprocessing, feature engineering, model training, and deployment
  • Develop and optimize LLM-based solutions leveraging Transformer architectures for enterprise applications
  • Implement RAG pipelines using embeddings and vector databases to integrate domain-specific knowledge into LLMs
  • Fine-tune LLMs on custom datasets (text corpora, Q&A, conversational data, structured-to-text) for specialized tasks
  • Ensure scalable deployment of ML & LLM models on cloud environments with monitoring, versioning, and performance optimization
  • Collaborate with data scientists, domain experts, and software engineers to deliver AI-driven business impact

What Were Looking For
Beyond technical skills, the ideal candidate should excel in :

  • Real-world AI application & deployment
  • Prompt engineering & model evaluation
  • Fine-tuning & customization of LLMs
  • Understanding of LLM internals & ecosystem tools
  • Creativity, problem-solving & innovation
  • Business alignment, security, and ethical AI practices

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