Lead ML Engineer

Practice - AIA - Artificial Intelligence and Analytics About AI & Analytics:

Artificial intelligence (AI) and the data it collects and analyzes will soon sit at the core of all intelligent, human-centric businesses. By decoding customer needs, preferences, and behaviors, our clients can understand exactly what services, products, and experiences their consumers need. Within AI & Analytics, we work to design the future—a future in which trial-and-error business decisions have been replaced by informed choices and data-supported strategies.

By applying AI and data science, we help leading companies to prototype, refine, validate, and scale their AI and analytics products and delivery models. Cognizant’s AIA practice takes insights that are buried in data and provides businesses a clear way to transform how they source, interpret and consume their information. Our clients need flexible data structures and a streamlined data architecture that quickly turns data resources into informative, meaningful intelligence.

Please note, this role is not able to offer visa transfer or sponsorship now or in the future

We are seeking a Lead ML Engineer to drive the design, development, and deployment of advanced machine learning and AI solutions leveraging Azure OpenAI, Azure Machine Learning, Snowflake, and Python. This role will serve as the technical leader for enterprise data science initiatives, owning model architecture, ML solution design, and AI platform integration. The ideal candidate will combine deep expertise in machine learning, cloud-native AI services, and software engineering with the ability to mentor teams and translate business challenges into scalable AI solutions.

This position requires a strong balance of hand-on engineering, technical leadership, and stakeholder engagement.

• Lead the end-to-end design, architecture, and implementation of machine learning and AI solutions using Azure OpenAI Services, Azure Machine Learning, and Python.
• Design and develop predictive, generative AI, and recommendation models to improve operational efficiency, customer experience, and business outcomes.
• Build and optimize machine learning pipelines including feature engineering, model training, validation, deployment, monitoring, and retraining.
• Integrate Azure OpenAI capabilities such as natural language processing, conversational AI, and generative AI into enterprise applications and workflows.
• Analyze large-scale structured and unstructured datasets to identify opportunities for business optimization, personalization, forecasting, and automation.
• Collaborate with product owners, data engineers, architects, and business stakeholders to define AI use cases and implementation roadmaps.
• Lead technical reviews, mentor data scientists and machine learning engineers, and establish engineering best practices for model development and deployment.
• Design scalable and secure MLOps workflows leveraging Git Hub, Docker, Azure Machine Learning, and cloud-native deployment patterns.
• Define model evaluation frameworks, responsible AI controls, governance standards, and risk mitigation processes.
• Evaluate emerging AI technologies, frameworks, and Azure capabilities to drive innovation and continuous improvement.
• Communicate technical findings and business impact to executive and non-technical stakeholders through compelling storytelling and data-driven insights.
• Ensure AI solutions comply with enterprise security, regulatory, privacy, and governance requirements.

• 8+ years of experience in Machine Learning, Data Science, Artificial Intelligence, or Advanced Analytics roles, with experience leading enterprise AI initiatives.
• Strong expertise in Python and machine learning libraries including Pandas, Scikit-learn, XGBoost, LightGBM, and PyTorch.
• Hands-on experience developing and deploying machine learning models in Azure Machine Learning environments.
• Experience designing and implementing Generative AI and Azure OpenAI solutions for enterprise use cases.
• Strong proficiency in SQL and experience working with Snowflake for analytics and machine learning workloads.
• Experien…