
MLOps Engineer
Required skills
- AWS
- distributed apps
- systems thinking
- ML Infrastructure
- pipelines
- platforms
- Python
- Typescript
- Transformers
- pytorch
Nice to have
- APIs
Role summary
Capgemini is seeking an MLOps Engineer to join their team in Westlake, TX. This onsite role requires a minimum of 3 years of experience putting Machine Learning models into production. The ideal candidate will have expertise in MLOps tools like Mlflow, Docker, and cloud platforms such as AWS, Google Cloud, or Azure. Strong knowledge of Machine Learning models, Large Language Models (LLMs) using tools like langchain, and Generative AI (GenAI) implementation is essential. The role also demands software engineering skills for writing clean, efficient code and experience with APIs for integration. The position emphasizes systems thinking and experience with ML infrastructure, pipelines, platforms, and tools.
Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you’d like, where you’ll be supported and inspired by a collaborative community of colleagues around the world, and where you’ll be able to reimagine what’s possible. Join us and help the world’s leading organizations unlock the value of technology and build a more sustainable, more inclusive world.
Location
The position is based in Westlake, TX, and requires candidates to work onsite.About the role you are considering
- Key Skills: AWS, distributed apps, systems thinking, ML Infrastructure , pipelines, platforms & tools, Python, Typescript, Transformers, pytorch, Jenkins, Git, Docker, vLLM, langGraph
- Min 3+ years of experience putting Machine Learning models into production.
- MLOps tools: Experience using Mlflow or similar tools for lifecycle management of machine learning models.
- Docker: Experience in using Docker to create reproducible and scalable environments.
- Machine Learning Models: Advanced knowledge in Machine Learning models and Large Language Models (LLM), using langchain or a similar tool.
- LLM Implementation: Experience in implementing LLMs using vector bases and Retrieval-Augmented Generation (RAG), as well as tuning models. Using GPTs, Llama, or any other LLM
- Solution Architecture Validation: Ability to perform solution architecture validations for LLMs. GenAIOps: Experience in putting Generative AI (GENAI) models into production and providing support to them.
- Experience with Cloud Computing: Familiarity with cloud computing platforms such as AWS, Google Cloud, or Azure for model deployment and scaling.
- Software Engineering Skills: The ability to write clean, efficient, and reusable code is essential in MLOps roles.
- Experience with APIs: Experience in developing and using APIs can be useful for integrating models into existing applications.
The base compensation range for this role in the posted location is: 70000 to 85000
Capgemini provides compensation range information in accordance with applicable national, state, provincial, and local pay transparency laws. The base compensation range listed for this position reflects the minimum and maximum target compensation Capgemini, in good faith, believes it may pay for the role at the time of this posting. This range may be subject to change as permitted by law.
The actual compensation offered to any candidate may fall outside of the posted range and will be determined based on multiple factors legally permitted in the applicable jurisdiction.
These may include, but are not limited to: Geographic location, Education and qualifications, Certifications and licenses, Relevant experience and skills, Seniority and performance, Market and business consideration, Internal pay equity.
It is not typical for candidates to be hired at or near the top of the posted compensation range.
In addition to base salary, this role may be eligible for additional compensation such as variable incentives, bonuses, or commissions, depending on the position and applicable laws.
Capgemini offers a comprehensive, non-negotiable benefits package to all regular, full-time employees. In the U.S. and Canada, available benefits are determined by local policy and eligibility and may include:
- Paid time off based on employee grade (A-F), defined by policy: Vacation: 12-25 days, depending on grade, Company paid holidays, Personal Days, Sick Leave
- Medical, dental, and vision coverage (or provincial healthcare coordination in Canada)
- Retirement savings plans (e.g., 401(k) in the U.S., RRSP in Canada)
- Life and disability insurance
- Employee assistance programs
- Other benefits as provided by local policy and eligibility
Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini’s discretion, consistent with applicable laws. The Company reserves the right to amend or withdraw compensation programs at any time, within the limits of applicable legislation.
Disclaimers
Capgemini is an Equal Opportunity Employer encouraging inclusion in the workplace. Capgemini also participates in the Partnership Accreditation in Indigenous Relations (PAIR) program which supports meaningful engagement with Indigenous communities across Canada by promoting fairness, accessibility, inclusion and respect. We value the rich cultural heritage and contributions of Indigenous Peoples and actively work to create a welcoming and respectful environment. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, sexual orientation, genetics, veteran status, marital status or any other characteristic protected by law.
This is a general description of the Duties, Responsibilities and Qualifications required for this position. Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed. Whenever necessary to provide individuals with disabilities an equal employment opportunity, Capgemini will consider reasonable accommodations that might involve varying job requirements and/or changing the way this job is performed, provided that such accommodation does not pose an undue hardship. Capgemini is committed to providing reasonable accommodation during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.
Please be aware that Capgemini 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.
Click the following link for more information on your rights as an Applicant in the United States. http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law
Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem.
Sample Capgemini interview questions
- 1
Design a system for managing a distributed feature flag system.
system designmedium - 2
Design a system for real-time processing of customer feedback.
system designmedium - 3
Develop a data processing engine for real-time analytics.
system designmedium - 4
Diameter of a Binary Tree Find the diameter of a binary tree. Input: root = [1,2] Output: 1 Explanation: The longest path is simply the single edge connecting the root node to its only child.
codingmedium - 5
Buildings with an Ocean View Find all buildings that have an ocean view. Input: heights = [1,2,3,4] Output: [3] Explanation: Since the ocean is to the right, only the rightmost tallest building (index 3) is not blocked by any others.
codingmedium
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