GenAI ML Engineer

Inclusion without Exception

Tata Consultancy Services (TCS) is an equal opportunity employer, and embraces diversity in race, nationality, ethnicity, gender, age, physical ability, neurodiversity, and sexual orientation, to create a workforce that reflects the societies we operate in. Our continued commitment to Culture and Diversity is reflected in our people stories across our workforce and implemented through equitable workplace policies and processes.

Tata Consultancy Services (BSE: 532540, NSE: TCS) is the technology partner of choice for industry-leading organizations worldwide. Since its inception in 1968, TCS has upheld the highest standards of innovation, engineering excellence and customer service.

It has set an aspiration to become the world's largest AI-led technology services company and is enabling its clients to transform themselves across the full AI stack, from infrastructure to intelligence.

Rooted in the heritage of the Tata Group, TCS is focused on creating long term value for its clients, its investors, its employees, and the community at large. With a highly skilled workforce spread across 56 countries and 194 service delivery centers across the world, the company has been recognized as a top employer in six continents. With the ability to rapidly apply and scale new technologies, the company has built long term partnerships with its clients. Many of these relationships have endured into decades and navigated every technology cycle, from mainframes in the 1970s to artificial intelligence today.

GenAI ML Engineer

Key Requirements

Senior level experience in AI/ML development

Experience in developing and deploying generative AI solutions and large language models

Design and implement generative AI models for text, code, and multimodal applications

Fine-tune, optimize, and deploy large language models such as GPT, Claude, and Llama

Develop training pipelines for custom generative models and foundation model adaptation

Expertise in Python for building ML applications, APIs, and services using frameworks such as PyTorch, TensorFlow, Hugging Face, and LangChain

Strong experience in prompt engineering for optimizing LLM-based applications

Implement model evaluation frameworks for performance, accuracy, and safety

Deploy and monitor ML models in production environments with proper scaling

Stay updated with latest GenAI research and implement advanced techniques

Build data preprocessing and feature engineering pipelines for ML workflows

Collaborate with cross-functional teams including product, engineering, and data science

Deep understanding of machine learning algorithms, neural networks, and model optimization

Hands-on experience with generative AI techniques including GANs, VAEs, diffusion models, and transformer architectures

Proficiency in large language models, fine-tuning strategies, and deployment approaches

Experience with MLOps practices including model versioning, monitoring, and production deployment

Knowledge of cloud platforms such as AWS, Azure, or GCP with ML services and GPU computing

Desired Skills

ML, GenAI, LLM, Python

Salary Range: CAD$90,000 - CAD$110,000

TCS does not use artificial intelligence tools for candidate screening or evaluat ion. This post is for a current vacancy. The hiring process includes an initial screening, followed by a technical evaluation and managerial discussion.

Tata Consultancy Services Canada Inc. is committed to meeting the accessibility needs of all individuals in accordance with the Accessibility for Ontarians with Disabilities Act (AODA) and the Ontario Human Rights Code (OHRC). Should you require accommodation during the recruitment and selection process, please inform Human Resources.

Thank you for your interest in TCS. Candidates that meet the qualifications for this position will be contacted within a 2-week period. We invite you to continue to apply for other opportunities that match your profile.

Location

Toronto, ON

Job Function

TECHNOLOGY

Role

Engineer

Job Id

413717

Desired Skills

Artificial Intelligence | DevOps | Machine Learning