Clinical Data ML Ops Engineer

Clinical Data ML Ops Engineer

Location - Hybrid @ North Chicago- 3 days a week

Key responsibilities:

Responsibilities may include the following and other duties may be assigned.

In new product design roles: develops and programs integrated software algorithms to structure, analyze and leverage data in product and systems applications in both structured and unstructured environments.

Well versed with LLM models and prompt engineering

Develops and communicates descriptive, diagnostic, predictive and prescriptive insights/algorithms.

In product/systems improvement projects: uses machine language and statistical modeling techniques such as decision trees, logistic regression, Bayesian analysis and others to develop and evaluate algorithms to improve product/system performance, quality, data management and accuracy.

In both theoretical development environments and specific product design, implementation and improvement environments, uses current programming language and technologies to translate algorithms and technical specifications into code.

Completes programming and implements efficiencies, performs testing and debugging.

Completes documentation and procedures for installation and maintenance.

Applies deep learning technologies to give computers the capability to visualize, learn and respond to complex situations.

Adapts machine learning to areas such as virtual reality, augmented reality, artificial intelligence, robotics and other products that allow users to have an interactive experience.

Can work with large scale computing frameworks, data analysis systems and modeling environments.

MLOps:

Design and implement cloud solutions, build MLOps on cloud (AWS, Azure, or GCP)

Build CI/CD pipelines orchestration by GitLab CI, GitHub Actions, Circle CI, Airflow or similar tools

Data science model review, run the code refactoring and optimization, containerization, deployment, versioning, and monitoring of its quality

Data science models testing, validation and tests automation

Communicate with a team of data scientists, data engineers and architect, document the processes

Required Qualifications/Skills:

Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS, MS Azure or GCP)

Experience with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., experience with Docker and Kubernetes, OpenShift

Programming languages like Python, Go, Ruby or Bash, good understanding of Linux, knowledge of frameworks such as scikit-learn, Keras, PyTorch, Tensorflow, etc.

Ability to understand tools used by data scientist and experience with software development and test automation

Fluent in English, good communication skills and ability to work in a team.

Salary and Other Compensation :

Applications will be accepted until Nov 16th 2025

The annual salary for this position is between $ 115-135K+ depending on experience and other qualifications of the successful candidate.

This position is also eligible for Cognizant's discretionary annual incentive program, based on performance and subject to the terms of Cognizant's applicable plans.

Benefits : Cognizant offers the following benefits for this position, subject to applicable eligibility requirements:

• Medical/Dental/Vision/Life Insurance
• Paid holidays plus Paid Time Off
• 401(k) plan and contributions
• Long-term/Short-term Disability
• Paid Parental Leave
• Employee Stock Purchase Plan

Disclaimer: The salary, other compensation, and benefits information is accurate as of the date of this posting. Cognizant reserves the right to modify this information at any time, subject to applicable law.

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 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 is one of the world's leading professional services companies, transforming clients' business, operating, and technology models for the digital era. Our unique industry-based, consultative approach helps clients envision, build, and run more innovative and efficient businesses. Headquartered in the U.S., Cognizant (a member of the NASDAQ-100 and one of Forbes World's Best Employers 2024) is consistently listed among the most admired companies in the world.

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 CareersNA2@cognizant.com 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.