Generative AI Engineer

TATA Consulting Services • Warren, MI

51d • $90,000 - $140,000

About The Position

Generative AI Engineer Programming: Expert-level proficiency in Python. ML Frameworks: Extensive experience with PyTorch (strongly preferred) and/or TensorFlow. LLMs & NLP: Hands-on experience working with Large Language Models (e.g., via OpenAI API, Hugging Face Transformers, LangChain, LlamaIndex, or custom models). Deep understanding of NLP concepts (tokenization, embeddings, attention mechanisms). Cloud & MLOps: Proven experience with cloud platforms (AWS, GCP, or Azure) and MLOps tools (e.g., Docker, Kubernetes, MLflow, Weights & Biases, TFX). Problem-Solving: Strong analytical and problem-solving skills with the ability to iterate quickly from experimentation to production-ready solutions Design & Development: Architect, train, fine-tune, and optimize large generative models (e.g., LLMs like GPT, diffusion models like Stable Diffusion, VAEs, GANs) for specific use cases. End-to-End Pipeline Ownership: Build robust, scalable data pipelines for pre-processing and curating massive training datasets. Model Deployment & MLOps: Implement and manage MLOps practices to deploy models into production, ensuring scalability, low latency, and high reliability. This includes containerization, API development, and continuous integration/continuous deployment (CI/CD). Performance Optimization: Apply advanced techniques like Retrieval-Augmented Generation (RAG), fine-tuning, quantization, and distillation to improve model efficiency, accuracy, and cost-effectiveness. Research & Innovation: Stay current with the latest academic research and open-source advancements in generative AI. Prototype new ideas and conduct experiments to validate their feasibility and impact. Collaboration: Work closely with product managers, data scientists, and software engineers to integrate generative AI capabilities into our products and platforms.

Requirements

• Expert-level proficiency in Python.
• Extensive experience with PyTorch (strongly preferred) and/or TensorFlow.
• Hands-on experience working with Large Language Models (e.g., via OpenAI API, Hugging Face Transformers, LangChain, LlamaIndex, or custom models).
• Deep understanding of NLP concepts (tokenization, embeddings, attention mechanisms).
• Proven experience with cloud platforms (AWS, GCP, or Azure) and MLOps tools (e.g., Docker, Kubernetes, MLflow, Weights & Biases, TFX).
• Strong analytical and problem-solving skills with the ability to iterate quickly from experimentation to production-ready solutions

Responsibilities

• Architect, train, fine-tune, and optimize large generative models (e.g., LLMs like GPT, diffusion models like Stable Diffusion, VAEs, GANs) for specific use cases.
• Build robust, scalable data pipelines for pre-processing and curating massive training datasets.
• Implement and manage MLOps practices to deploy models into production, ensuring scalability, low latency, and high reliability. This includes containerization, API development, and continuous integration/continuous deployment (CI/CD).
• Apply advanced techniques like Retrieval-Augmented Generation (RAG), fine-tuning, quantization, and distillation to improve model efficiency, accuracy, and cost-effectiveness.
• Stay current with the latest academic research and open-source advancements in generative AI. Prototype new ideas and conduct experiments to validate their feasibility and impact.
• Work closely with product managers, data scientists, and software engineers to integrate generative AI capabilities into our products and platforms.

Benefits

• Discretionary Annual Incentive.
• Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
• Family Support: Maternal & Parental Leaves.
• Insurance Options: Auto & Home Insurance, Identity Theft Protection.
• Convenience & Professional Growth: Commuter Benefits & Certification & Training Reimbursement.
• Time Off: Vacation, Time Off, Sick Leave & Holidays.
• Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Industry: Professional, Scientific, and Technical Services
• Education Level: No Education Listed
• Number of Employees: 5,001-10,000 employees