MLOps Engineer

Sogeti is a leading provider of professional technology services, specializing in Application Management, Infrastructure Management and High-Tech Engineering. Sogeti offers cutting-edge solutions around Testing, Business Intelligence, Mobility, Cloud and Security, combining world class methodologies and the global delivery model, Rightshore®. Sogeti brings together more than 20,000 professionals in 15 countries and is present in over 100 locations in Europe, the US and India. Sogeti is a wholly-owned subsidiary of Cap Gemini S.A., listed on the Paris Stock Exchange.

At Sogeti USA, we are committed to building a long and enduring relationship with our employees and to creating an environment that rewards and empowers. Our mission is to constantly exceed our employees' expectations in the same way that we strive to exceed our clients' expectations. We offer an environment that celebrates innovation and helps you to achieve a good balance between your professional and personal life. We strive to be an employer of choice!

What You’ll Do

We are seeking a skilled and motivated MLOps Engineer to join our Data & AI team, with a focus on building and scaling machine learning operations on Azure Databricks. You will be responsible for operationalizing ML models, optimizing pipelines, and establishing CI/CD workflows across the Azure ecosystem to accelerate AI deployment and innovation. Minimum education qualification

Bachelor's Degree in Computer Science, Computer Engineering, MIS or related field. Key Responsibilities

Design, build, and maintain robust MLOps pipelines on Azure Databricks for scalable model training, deployment, and monitoring.

Implement CI/CD workflows using tools such as Azure DevOps, MLflow, and GitHub Actions.

Operationalize machine learning models (batch and real-time) leveraging Delta Lake and Model Serving.

Automate data and model versioning, testing, and lineage tracking across environments.

Collaborate with Data Scientists, Data Engineers, and DevOps teams to integrate ML workflows into the broader data ecosystem.

Establish and maintain monitoring solutions for model performance and data drift.

Ensure compliance with governance, security, and data privacy standards in model lifecycle management. Required Skills & Experience

3+ years of experience in MLOps, ML engineering, or related fields.

Strong knowledge of Azure ecosystem (Azure ML, Azure DevOps, Key Vault, Storage, Functions).

Experience building ML pipelines using Python, PySpark, and Databricks notebooks.

Familiarity with CI/CD tools and Git-based workflows.

Strong debugging, automation, and performance optimization skills. The benefits our employees enjoy:

401(k) Savings Plan- Matched 150% up to 6%. (Our 401k is in the top 1% of 401(k) plans offered in the US!)

Medical/Prescription/Dental/Vision Coverage!

Low-premium and deductible. Plan with free preventive care.

$12,000 in Tuition Reimbursement

100% Company-paid mobile phone plan

Personal Time Off (PTO)- Ensuring a balance of work and home life Please be aware that Capgemini Sogeti may capture your image (video or screenshot) during the interview process and that image may be used for verification, including during the hiring and onboarding process