Cognizant
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Clinical Data ML Ops Engineer
role at
Cognizant
Job Title Clinical Data ML Ops Engineer
Location Hybrid @ North Chicago - 3 days a week
Key Responsibilities
Develop 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.
Provide descriptive, diagnostic, predictive, and prescriptive insights/algorithms.
Apply machine learning and statistical modeling techniques (decision trees, logistic regression, Bayesian analysis, etc.) to improve product/system performance, quality, data management, and accuracy.
Translate algorithms and technical specifications into code, complete programming, implement efficiencies, and perform testing and debugging.
Document procedures for installation and maintenance.
Apply deep learning technologies to enable computers to visualize, learn, and respond to complex situations.
Adapt machine learning to virtual reality, augmented reality, AI, robotics, and related products for interactive user experiences.
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 orchestrated by GitLab CI, GitHub Actions, CircleCI, Airflow, or similar tools.
Review data science models, refactor and optimize code, containerize, deploy, version, and monitor quality.
Test, validate, and automate testing of data science models.
Communicate with data scientists, data engineers, and architects and document processes.
Required Qualifications/Skills
Design and implement cloud solutions and build MLOps pipelines on AWS, Azure, or GCP.
Experience with MLOps frameworks (Kubeflow, MLFlow, DataRobot, Airflow, etc.), Docker, Kubernetes, OpenShift.
Programming in Python, Go, Ruby, or Bash; strong Linux fundamentals; familiarity with scikit‑learn, Keras, PyTorch, TensorFlow, etc.
Understand data scientist tools and experience with software development and test automation.
Fluent in English with strong communication skills and team orientation.
Salary and Other Compensation Applications will be accepted until Nov 16th 2025.
Annual salary: $115,000 - $135,000+ depending on experience and qualifications.
Eligible for Cognizant’s discretionary annual incentive program based on performance.
Benefits
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.
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Clinical Data ML Ops Engineer
role at
Cognizant
Job Title Clinical Data ML Ops Engineer
Location Hybrid @ North Chicago - 3 days a week
Key Responsibilities
Develop 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.
Provide descriptive, diagnostic, predictive, and prescriptive insights/algorithms.
Apply machine learning and statistical modeling techniques (decision trees, logistic regression, Bayesian analysis, etc.) to improve product/system performance, quality, data management, and accuracy.
Translate algorithms and technical specifications into code, complete programming, implement efficiencies, and perform testing and debugging.
Document procedures for installation and maintenance.
Apply deep learning technologies to enable computers to visualize, learn, and respond to complex situations.
Adapt machine learning to virtual reality, augmented reality, AI, robotics, and related products for interactive user experiences.
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 orchestrated by GitLab CI, GitHub Actions, CircleCI, Airflow, or similar tools.
Review data science models, refactor and optimize code, containerize, deploy, version, and monitor quality.
Test, validate, and automate testing of data science models.
Communicate with data scientists, data engineers, and architects and document processes.
Required Qualifications/Skills
Design and implement cloud solutions and build MLOps pipelines on AWS, Azure, or GCP.
Experience with MLOps frameworks (Kubeflow, MLFlow, DataRobot, Airflow, etc.), Docker, Kubernetes, OpenShift.
Programming in Python, Go, Ruby, or Bash; strong Linux fundamentals; familiarity with scikit‑learn, Keras, PyTorch, TensorFlow, etc.
Understand data scientist tools and experience with software development and test automation.
Fluent in English with strong communication skills and team orientation.
Salary and Other Compensation Applications will be accepted until Nov 16th 2025.
Annual salary: $115,000 - $135,000+ depending on experience and qualifications.
Eligible for Cognizant’s discretionary annual incentive program based on performance.
Benefits
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.
#J-18808-Ljbffr