We are seeking a self-driven Machine Learning Engineer with a strong background in developing AI/ML solutions and extensive experience working within a microservice environment. The ideal candidate will have expertise in developing these solutions on GCP, with deep knowledge in developing products in Python, Kubernetes, and strong familiarity with orchestration technologies like KFP or Airflow. The candidate must also have experience with GCP suite of tools, such as Vertex AI, BigQuery, and Dataflow. This role requires a deep understanding of computer science and machine learning engineering principles.

We are Cognizant Artificial Intelligence:

Digital technologies, including analytics and AI, give companies a once-in-a-generation opportunity to perform orders of magnitude better than ever before. However, clients need new business models built from analyzing customers and business operations at every angle to really understand them. With the power to apply artificial intelligence and data science to business decisions via enterprise data management solutions, we help leading companies prototype, refine, validate, and scale the most desirable products and delivery models to enterprise scale within weeks.

In this role, you will:

• Design robust cloud solutions in GCP that will service our client’s intelligence and data solutions.

• Develop and deploy GenAI models using LangChain.

• Develop and deploy models and services in managed Kubernetes Framework (Anthos).

• Enhance and optimize the performance of containerized applications.

• Develop and deploy batch predictions using Dataflow, KFP and Vertex AI.

• Demonstrate expertise in Agile methodologies, with a strong emphasis on backlog management and sprint planning to ensure efficient project progression and delivery.

• Cross-functional collaboration with other machine learning engineers and data scientists to drive requirements and create new models.

• Implement and maintain ongoing prediction pipelines using tools like Kubernetes, Airflow, KFP, and Vertex AI.

• Ensure best practices in ML engineering, including code quality, testing, and documentation.

• Foster a culture of innovation, continuous learning, and knowledge sharing within the team.

• Understand and champion Software Development Life Cycle (SDLC) as well as the Model Development Life Cycle (MDLC).

• Estimate the effort required for implementing machine learning features, enhancements, and bug fixes, considering factors such as complexity, data volume, and integration points.

• Collaborate with data scientists to train, guide, and support processes to ensure security and address vulnerabilities.

What you’ll need to succeed (required skills):

· 8-12 years of relevant experience in Software Engineering or ML/AI engineering with a focus on cloud technologies.

· Must have 4+ years of industry experience using machine learning to solve real-world problems with large datasets and be comfortable with tools for high-scale data ingestion, transformation, analysis, and prediction.

· Extensive expertise with modern deep learning frameworks (PyTorch, TensorFlow, JAX) and advanced LLM architectures including transformer models, attention mechanisms, and multimodal AI systems.

· Proficiency in Python, FastAPI, GCP, Cloud Architecture, KFP, Vertex AI, and Kubernetes.

· Strong experience with containerization and orchestration using Kubernetes.

· Solid understanding of machine learning concepts, algorithms and machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).

· Strong understanding of Generative AI concepts and experience with LangChain.

· Strong communication skills and the ability to collaborate effectively with cross-functional teams.

What will help you stand out (preferred skills):

• Familiarity with the LLM ecosystem, prompt engineering techniques, evaluation and observability to improve the user experience.

• Experience with leading large-scale multi-engineer projects.

At Cognizant, we're eager to meet people who believe in our mission and can make an impact in various ways. We strongly encourage you to apply even if you only meet the required skills listed. Consider what transferrable experience and skills make you a unique applicant and help us see how you'd be beneficial to this role.

Cognizant will only consider applicants for this position who are legally authorized to work in Canada without requiring employer sponsorship, now or at any time in the future.

Working Arrangements:

We believe hybrid work is the way forward as we strive to provide flexibility wherever possible. Based on this role’s business requirements, this is a hybrid position requiring 1 day a week in a Cognizant or client office in Toronto, ON . Regardless of your working arrangement, we are here to support a healthy work-life balance through our various well-being programs.

Note: The working arrangements for this role are accurate as of the date of posting. This may change based on the project you’re engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.