We are seeking a skilled machine learning platform engineer (MLOps) to join our agile platform team. In this role, you’ll contribute across the entire lifecycle - from concept to deployment and collaborate closely with cross-functional teams to deliver high-quality digital solutions. Further, you will drive the orchestration of advanced agentic workflows to enable autonomous, AI-driven systems. You will be responsible for engineering robust data pipelines, establishing comprehensive model management lifecycles, overseeing all foundational platform-level AI integrations.
Job Responsibilities
Design, develop and deploy machine learning solutions and services
Implement end-to-end machine learning pipelines from data ingestion to training and model serving
Operationalize LLMs, embeddings, and multi-agent systems in real-world applications
Manage the machine learning and model lifecycle (experimentation, registry, deployment)
Oversee the model promotion lifecycle, coordinating validation gates and approval workflows to safely deploy new model versions from stating to production
Containerize applications using Docker and orchestrate them via Kubernetes
Build and maintain CI/CD pipelines for ML models and LLM applications
Collaborate with data scientists to refactor research code into production-ready Python code
Monitor model performance, data drift, and performance in production
Assess and integrate AI solutions ensuring optimal performance and reliability
Design and implement production grade RAG systems
Collaborate with infrastructure teams, data engineers, data scientists, and other stakeholders to integrate machine learning solutions into existing systems and processes
Participate in code reviews, testing, and debugging to ensure the quality and reliability of machine learning solutions
Job Requirements
Competencies
Strong problem-solving and analytical skills, with the ability to think critically and creatively about complex challenges
Excellent communication and collaboration skills, with the ability to work effectively with cross-functional teams and stakeholders at all levels of the organization
Ability to manage personal workloads effectively, to prioritize tasks, manage timelines, and deliver high-quality results on schedule
Continuous learning mindset, with a passion for staying up to date with the latest advancements in machine learning and artificial intelligence
Attention to detail and commitment to producing high-quality, reliable, and maintainable code
Skills requirements
Advanced proficiency in Python programming with a focus on writing clean, testable and efficient code
DevOps & Containers: Proficient with Docker for containerization and working knowledge of Kubernetes (k8s) for orchestration
Practical understanding of GPU architecture and cloud compute instances to optimize resource allocation for training and inference workloads
MLOPS tools: hands on experience with MLflow (or similar tools like weights & biases) for experiment tracking and model registry
Proven experience working with Large Language Models (LLMs)
Good understanding of AI agents & agentic workflows, LLM orchestration frameworks and reasoning patterns
Experience with data preprocessing, feature engineering, and model selection and evaluation techniques
Hands-on experience with CI/CD pipelines (GitLab, Jenkins)
Knowledge of statistical and mathematical concepts relevant to machine learning, such as probability, linear algebra, and optimization
Excellent problem-solving and debugging skills, with the ability to identify and resolve issues quickly and effectively
Relevant work experience in machine learning, data science or a related field
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What we offer
- The chance to work with impact. Here, you’re empowered to bring your biggest thinking to help our company and clients improve everyday life.
- Ownership over your career. Stay at the top of your game through our award-winning learning and development ecosystem. And when your ambitions change or we offer new opportunities, we help you pivot by providing reskilling, on-the-job learning and guidance to find new roles that might be a better fit.
- The opportunity to thrive on a high caliber team with heart. We celebrate each other’s experiences and perspectives and promote a sense of belonging through our affinity groups and diversity and inclusion initiatives.
- A comprehensive total rewards package, including a competitive salary and a pension plan with matching contributions.
- Flexible health and financial benefits to support you and your eligible dependents—from day one.
- True work-life balance. Be at your best through paid time off, flexible work arrangements, volunteering opportunities, social events, and so much more.
About us
Cognizant (Nasdaq: CTSH) is an AI Builder and technology services provider, building the bridge between AI investment and enterprise value by building full-stack AI solutions for our clients. Our deep industry, process and engineering expertise enables us to build an organization’s unique context into technology systems that amplify human potential, realize tangible returns and keep global enterprises ahead in a fast-changing world. See how at www.cognizant.com or @cognizant.
Other employment-related information
Cognizant is an equal opportunity employer. Your application and candidacy will not be considered based on race, color, sex, religion, creed, sexual orientation, gender identity, national origin, disability, genetic information, pregnancy, veteran status or any other characteristic protected by federal, provincial or local laws.
If you have a disability that requires reasonable accommodation to search for a job opening or submit an application, please email [email protected] with your request and contact information.
Language requirements vary depending on roles, but we ask that all candidates have basic English proficiency for company-wide communications purposes. For roles based in Quebec, professional English proficiency is required, as you’ll deliver services to and collaborate with stakeholders outside the province who may not speak French.
