Machine Learning Engineer

About Genpact

Ready to build the future with AI?

At Genpact, we don’t just keep up with technology—we set the pace. AI and digital innovation are redefining industries, and we’re leading the charge. Genpact’s AI Gigafactory, our industry-first accelerator, is an example of how we’re scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to agentic AI, our breakthrough solutions tackle companies’ most complex challenges.

If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what’s possible, this is your moment.

Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting‑edge solutions – we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Get to know us at genpact.com and on LinkedIn, X, YouTube, and Facebook.

Job Title

Senior Machine Learning Engineer (Cloud & Data Platform)

Location

Montreal, Canada – Hybrid.

Job Description

We are seeking a highly capable Senior Machine Learning Engineer to support the modernization of enterprise analytics and modeling platforms. This role focuses on migrating and transforming legacy data and machine learning workflows into scalable, cloud‑native architectures while improving performance, reliability, and engineering standards.

The ideal candidate combines strong ML engineering expertise with deep experience in distributed data processing and cloud data platforms.

Responsibilities

🔹 Machine Learning Engineering

• Design, develop, and deploy scalable machine learning models using modern frameworks (e.g., PyTorch)
• Re‑engineer and optimize legacy models into efficient, production‑grade implementations
• Improve model performance, scalability, and reproducibility
• Support model validation, benchmarking, and certification processes
• Ensure full traceability and documentation of model logic and outputs

🔹 Data Platform & Pipeline Engineering

• Design and optimize distributed data pipelines using Spark‑based platforms (e.g., Databricks)
• Build and refactor ETL/ELT workflows for performance and scalability
• Implement data models within modern cloud data warehouses (e.g., Snowflake)
• Apply best practices for cloud‑native data architecture
• Standardize reusable utilities and frameworks for analytics workflows

🔹 Cloud Migration & Modernization

• Participate in migration of on‑prem or legacy analytics platforms to cloud ecosystems
• Refactor existing codebases to align with modern engineering and DevOps standards
• Leverage cloud compute capabilities (including GPU acceleration where applicable)
• Support scheduling and orchestration of data and ML workflows

🔹 Testing, Validation & Governance

• Conduct rigorous testing and validation to ensure data and model accuracy
• Perform parallel runs and benchmarking when modernizing systems
• Collaborate with governance, risk, and compliance stakeholders
• Maintain high standards of documentation and reproducibility

Why join Genpact?

• Lead AI‑first transformation – Build and scale AI solutions that redefine industries
• Make an impact – Drive change for global enterprises and solve business challenges that matter
• Accelerate your career — Gain hands‑on experience, world‑class training, mentorship, and AI certifications to advance your skills
• Grow with the best – Learn from top engineers, data scientists, and AI experts in a dynamic, fast-m