Generative AI Engineer

Tata Consultancy Services; Noida; On-site; INR 100,000 - 150,000; Full time

Job summary

A leading IT consulting firm is seeking a Generative AI Engineer to lead the development of advanced AI models. This position involves working with cutting-edge technologies to design and optimize machine learning systems, enhance AI capabilities, and collaborate with diverse teams. Ideal candidates should have experience in Agile development and a solid grasp of AI models and pipelines.

Qualifications

• Mid-senior level role in AI/ML for model training and engineering tasks.
• Experience in developing AI pipelines and optimizing pre-trained models.
• Knowledge of Agile/Scrum practices and collaboration with cross-functional teams.

Responsibilities

• Design, train, and optimize generative AI models for various applications.
• Develop end-to-end AI pipelines including data preprocessing and deployment.
• Collaborate with teams to enhance models and ensure compliance with AI ethics.

Skills

Generative AI Model Development

NLP

Deep Learning

Agile Development

Collaboration

Tools

PyTorch

TensorFlow

JAX

AWS

Docker

Kubernetes

Job description

Direct message the job poster from Tata Consultancy Services

• Generative AI Model Development: Design, train, and fine-tune LLMs (GPT, LLaMA, Claude), diffusion models, and multimodal AI systems for various applications.
• NLP & Deep Learning Expertise: Implement and optimize Transformer-based architectures (BERT, T5, GPT, etc.) for text generation, summarization, and embeddings.
• AI Pipeline Engineering: Develop end-to-end AI pipelines, including data preprocessing, model training, inference, and deployment using PyTorch, TensorFlow, or JAX.
• Agile Development: Work in an Agile/Scrum environment, participating in standups, sprint planning, and retrospectives to iteratively develop AI-driven products.
• Fine-tuning & Optimization: Optimize pre-trained models through LoRA, PEFT, quantization, and distillation for efficiency and cost-effectiveness.
• Cloud & MLOps Integration: Deploy AI models on AWS using Kubernetes, Docker, FastAPI, and serverless architectures.
• Vector Databases & Retrieval-Augmented Generation (RAG): Work with FAISS, ChromaDB, Weaviate, or Pinecone to enhance generative models with retrieval-augmented techniques.
• AI Security & Ethics: Implement safeguards against bias, hallucinations, adversarial attacks, and ensure compliance with AI governance frameworks (e.g., GDPR, HIPAA).
• Experimentation & Research: Stay up-to-date with the latest AI advancements, conduct A/B testing, and experiment with new zero-shot, few-shot, and fine-tuning techniques.
• Collaboration & Mentorship: Work with cross-functional teams (data scientists, software engineers, product teams) and mentor junior AI engineers.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology

• Industries

  IT Services and IT Consulting

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