Job Description
Qualifications
Strong experience with Unity Catalog in Databricks for managing data assets and access control
Hands-on experience working with Databricks Feature Store or similar solutions
Knowledge of building and maintaining scalable ETL pipelines in Databricks
Familiarity with Azure tools like Azure Cosmos DB and ACR
Understanding of machine learning workflows and how feature stores fit into the pipeline
Strong problem-solving skills and a collaborative attitude
Proficiency in Python and Spark for data engineering tasks
Experience with monitoring tools like Splunk or Datadog to ensure system reliability
Familiarity with AKS for deploying and handling containers
Benefits
Flexible work
Healthcare including dental, vision, mental health, and well-being programs
Financial well-being programs such as 401(k) and Employee Share Ownership Plan
Paid time off and paid holidays
Paid parental leave
Family building benefits like adoption assistance, surrogacy, and cryopreservation
Social well-being benefits like subsidized back-up child/elder care and tutoring
Mentoring, coaching and learning programs
Employee Resource Groups
Disaster Relief
The base salary range for the tagged location is $76,200,-$156,310
This role may be eligible for other compensation including variable compensation, bonus, or commission
Full time regular employees are eligible for paid time off, medical/dental/vision insurance, 401(k), and any other benefits to eligible employees
Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable
The amount and availability of any bonus, commission, or any other form of compensation that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company’s sole discretion, consistent with the law
Responsibilities
We are looking for an ML engineer with expertise in Unity Catalog and Feature Store in Databricks to help us build and maintain a solid foundation for our data and machine learning workflows
You will work on prioritizing data, managing access, and enabling machine learning models to operate efficiently in production
Set up and manage Unity Catalog in Databricks to organize and secure data access across teams
Design and operationalize Feature Stores to support machine learning models in production
Build efficient data pipelines to process and serve features to ML workflows
Collaborate with teams using Databricks, Azure Cosmos DB, and other Azure tools to integrate data solutions
Monitor and optimize the performance of pipelines and feature stores"
Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed
Job description
Job Description
We are looking for an ML engineer with expertise in Unity Catalog and Feature Store in Databricks to help us build and maintain a solid foundation for our data and machine learning workflows. You will work on prioritizing data, managing access, and enabling machine learning models to operate efficiently in production
Key Responsibilities
• Set up and manage Unity Catalog in Databricks to organize and secure data access across teams
• Design and operationalize Feature Stores to support machine learning models in production
• Build efficient data pipelines to process and serve features to ML workflows
• Collaborate with teams using Databricks, Azure Cosmos DB, and other Azure tools to integrate data solutions
• Monitor and optimize the performance of pipelines and feature stores"
Required Skills
• Strong experience with Unity Catalog in Databricks for managing data assets and access control
• Hands-on experience working with Databricks Feature Store or similar solutions
• Knowledge of building and maintaining scalable ETL pipelines in Databricks
• Familiarity with Azure tools like Azure Cosmos DB and ACR
• Understanding of machine learning workflows and how feature stores fit into the pipeline
• Strong problem-solving skills and a collaborative attitude
• Proficiency in Python and Spark for data engineering tasks
• Experience with monitoring tools like Splunk or Datadog to ensure system reliability
• Familiarity with AKS for deploying and handling containers
Life at Capgemini
Capgemini Supports All Aspects Of Your Well-being Throughout The Changing Stages Of Your Life And Career. For Eligible Employees, We Offer
• Flexible work
• Healthcare including dental, vision, mental health, and well-being programs
• Financial well-being programs such as 401(k) and Employee Share Ownership Plan
• Paid time off and paid holidays
• Paid parental leave
• Family building benefits like adoption assistance, surrogacy, and cryopreservation
• Social well-being benefits like subsidized back-up child/elder care and tutoring
• Mentoring, coaching and learning programs
• Employee Resource Groups
• Disaster Relief
About Capgemini Engineering
World leader in engineering and R&D services, Capgemini Engineering combines its broad industry knowledge and cutting-edge technologies in digital and software to support the convergence of the physical and digital worlds. Coupled with the capabilities of the rest of the Group, it helps clients to accelerate their journey towards Intelligent Industry. Capgemini Engineering has more than 55,000 engineer and scientist team members in over 30 countries across sectors including Aeronautics, Space, Defense, Naval, Automotive, Rail, Infrastructure & Transportation, Energy, Utilities & Chemicals, Life Sciences, Communications, Semiconductor & Electronics, Industrial & Consumer, Software & Internet.
Capgemini Engineering is an integral part of the Capgemini Group, a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided every day by its purpose of unleashing human energy through technology for an inclusive and sustainable future. 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, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2026 global revenues of €22.5 billion.
Get the Future You Want | www.capgemini.com
Disclaimer
Capgemini is an Equal Opportunity Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, ****** 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 accommodations do not pose an undue hardship.
Capgemini is committed to providing reasonable accommodations during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.
Click the following link for more information on your rights as an Applicant http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law
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.
Applicants for employment in the US must have valid work authorization that does not now and/or will not in the future require sponsorship of a visa for employment authorization in the US by Capgemini.
Capgemini discloses salary range information in compliance with state and local pay transparency obligations. The disclosed range represents the lowest to highest salary we, in good faith, believe we would pay for this role at the time of this posting, although we may ultimately pay more or less than the disclosed range, and the range may be modified in the future. The disclosed range takes into account the wide range of factors that are considered in making compensation decisions including, but not limited to, geographic location, relevant education, qualifications, certifications, experience, skills, seniority, performance, sales or revenue-based metrics, and business or organizational needs. At Capgemini, it is not typical for an individual to be hired at or near the top of the range for their role. The base salary range for the tagged location is $76,200,-$156,310. This role may be eligible for other compensation including variable compensation, bonus, or commission. Full time regular employees are eligible for paid time off, medical/dental/vision insurance, 401(k), and any other benefits to eligible employees. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, or any other form of compensation that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company’s sole discretion, consistent with the law
Strong experience with Unity Catalog in Databricks for managing data assets and access control
Hands-on experience working with Databricks Feature Store or similar solutions
Knowledge of building and maintaining scalable ETL pipelines in Databricks
Familiarity with Azure tools like Azure Cosmos DB and ACR
Understanding of machine learning workflows and how feature stores fit into the pipeline
Strong problem-solving skills and a collaborative attitude
Proficiency in Python and Spark for data engineering tasks
Experience with monitoring tools like Splunk or Datadog to ensure system reliability
Familiarity with AKS for deploying and handling containers
Benefits
Flexible work
Healthcare including dental, vision, mental health, and well-being programs
Financial well-being programs such as 401(k) and Employee Share Ownership Plan
Paid time off and paid holidays
Paid parental leave
Family building benefits like adoption assistance, surrogacy, and cryopreservation
Social well-being benefits like subsidized back-up child/elder care and tutoring
Mentoring, coaching and learning programs
Employee Resource Groups
Disaster Relief
The base salary range for the tagged location is $76,200,-$156,310
This role may be eligible for other compensation including variable compensation, bonus, or commission
Full time regular employees are eligible for paid time off, medical/dental/vision insurance, 401(k), and any other benefits to eligible employees
Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable
The amount and availability of any bonus, commission, or any other form of compensation that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company’s sole discretion, consistent with the law
Responsibilities
We are looking for an ML engineer with expertise in Unity Catalog and Feature Store in Databricks to help us build and maintain a solid foundation for our data and machine learning workflows
You will work on prioritizing data, managing access, and enabling machine learning models to operate efficiently in production
Set up and manage Unity Catalog in Databricks to organize and secure data access across teams
Design and operationalize Feature Stores to support machine learning models in production
Build efficient data pipelines to process and serve features to ML workflows
Collaborate with teams using Databricks, Azure Cosmos DB, and other Azure tools to integrate data solutions
Monitor and optimize the performance of pipelines and feature stores"
Physical, mental, sensory or environmental demands may be referenced in an attempt to communicate the manner in which this position traditionally is performed
Job description
Job Description
We are looking for an ML engineer with expertise in Unity Catalog and Feature Store in Databricks to help us build and maintain a solid foundation for our data and machine learning workflows. You will work on prioritizing data, managing access, and enabling machine learning models to operate efficiently in production
Key Responsibilities
• Set up and manage Unity Catalog in Databricks to organize and secure data access across teams
• Design and operationalize Feature Stores to support machine learning models in production
• Build efficient data pipelines to process and serve features to ML workflows
• Collaborate with teams using Databricks, Azure Cosmos DB, and other Azure tools to integrate data solutions
• Monitor and optimize the performance of pipelines and feature stores"
Required Skills
• Strong experience with Unity Catalog in Databricks for managing data assets and access control
• Hands-on experience working with Databricks Feature Store or similar solutions
• Knowledge of building and maintaining scalable ETL pipelines in Databricks
• Familiarity with Azure tools like Azure Cosmos DB and ACR
• Understanding of machine learning workflows and how feature stores fit into the pipeline
• Strong problem-solving skills and a collaborative attitude
• Proficiency in Python and Spark for data engineering tasks
• Experience with monitoring tools like Splunk or Datadog to ensure system reliability
• Familiarity with AKS for deploying and handling containers
Life at Capgemini
Capgemini Supports All Aspects Of Your Well-being Throughout The Changing Stages Of Your Life And Career. For Eligible Employees, We Offer
• Flexible work
• Healthcare including dental, vision, mental health, and well-being programs
• Financial well-being programs such as 401(k) and Employee Share Ownership Plan
• Paid time off and paid holidays
• Paid parental leave
• Family building benefits like adoption assistance, surrogacy, and cryopreservation
• Social well-being benefits like subsidized back-up child/elder care and tutoring
• Mentoring, coaching and learning programs
• Employee Resource Groups
• Disaster Relief
About Capgemini Engineering
World leader in engineering and R&D services, Capgemini Engineering combines its broad industry knowledge and cutting-edge technologies in digital and software to support the convergence of the physical and digital worlds. Coupled with the capabilities of the rest of the Group, it helps clients to accelerate their journey towards Intelligent Industry. Capgemini Engineering has more than 55,000 engineer and scientist team members in over 30 countries across sectors including Aeronautics, Space, Defense, Naval, Automotive, Rail, Infrastructure & Transportation, Energy, Utilities & Chemicals, Life Sciences, Communications, Semiconductor & Electronics, Industrial & Consumer, Software & Internet.
Capgemini Engineering is an integral part of the Capgemini Group, a global leader in partnering with companies to transform and manage their business by harnessing the power of technology. The Group is guided every day by its purpose of unleashing human energy through technology for an inclusive and sustainable future. 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, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2026 global revenues of €22.5 billion.
Get the Future You Want | www.capgemini.com
Disclaimer
Capgemini is an Equal Opportunity Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to race, national origin, gender identity/expression, age, religion, disability, ****** 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 accommodations do not pose an undue hardship.
Capgemini is committed to providing reasonable accommodations during our recruitment process. If you need assistance or accommodation, please reach out to your recruiting contact.
Click the following link for more information on your rights as an Applicant http://www.capgemini.com/resources/equal-employment-opportunity-is-the-law
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.
Applicants for employment in the US must have valid work authorization that does not now and/or will not in the future require sponsorship of a visa for employment authorization in the US by Capgemini.
Capgemini discloses salary range information in compliance with state and local pay transparency obligations. The disclosed range represents the lowest to highest salary we, in good faith, believe we would pay for this role at the time of this posting, although we may ultimately pay more or less than the disclosed range, and the range may be modified in the future. The disclosed range takes into account the wide range of factors that are considered in making compensation decisions including, but not limited to, geographic location, relevant education, qualifications, certifications, experience, skills, seniority, performance, sales or revenue-based metrics, and business or organizational needs. At Capgemini, it is not typical for an individual to be hired at or near the top of the range for their role. The base salary range for the tagged location is $76,200,-$156,310. This role may be eligible for other compensation including variable compensation, bonus, or commission. Full time regular employees are eligible for paid time off, medical/dental/vision insurance, 401(k), and any other benefits to eligible employees. Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, or any other form of compensation that are allocable to a particular employee remains in the Company's sole discretion unless and until paid and may be modified at the Company’s sole discretion, consistent with the law
💡 Quick Summary
Seeking a career-building opportunity? The Machine Learning Engineer position is now open for candidates interested in the IT Engineer & Developer Jobs sector. This role in Washington offers a professional environment and growth potential.
Requirement Snapshot: Candidates should possess basic communication skills, a proactive attitude, and the ability to work in a team. Experience in IT Engineer & Developer Jobs is a plus.
