Machine Learning Engineer - Capgemini
Dallas, TX
About the Job
Job Title: Senior Machine Learning Engineer
Job Location: Hybrid (preferred base cities - Atlanta, NYC, Dallas, Houston, Chicago, San Fran, and Seattle)
Job Description: As a Senior Machine Learning Engineer, you will lead the development and implementation of sophisticated data engineering solutions to support the deployment and optimization of AI models. Your role will involve demonstrating extensive experience to design robust, scalable, and innovative data architectures that align with the unique requirements of Artificial Intelligence applications.
Key Responsibilities:
+ The Machine Learning Engineer will be responsible for architectural design and planning, advanced data pipelines, model integration and optimization, scalability, performance and research and innovation supporting production AI systems.
+ Build and maintain data engineering solutions on cloud platforms using hyperscaler services (GPC, AWS, Azure).
+ Design, develop, and maintain data pipelines to efficiently collect, process, and load data from various sources into data storage systems (e.g., data warehouses, data lakes).
+ Develop and maintain data models and schema designs to support efficient data storage and retrieval.
+ Use hyperscaler technologies to support data needs for expansion of Machine Learning/Data Science capabilities including generative AI.
+ Implement data validation and data cleansing processes to ensure data quality and consistency.
+ Design, develop, and implement scalable data pipelines and ETL/ELT processes using Python, PySpark and API integrations.
+ Monitor ETL jobs, troubleshoot issues, and ensure data processing efficiency.
+ Administer and optimize databases, ensuring performance, scalability, and data security.
+ Collaborate with multi-functional teams to understand data requirements and integrate data into various applications and analytics platforms.
+ Collaborate with data scientists and analysts to understand data requirements and translate them into scalable, high performant data pipeline solutions.
+ Ensure compliance with data privacy and security regulations.
+ Optimize data systems for scalability and performance, anticipating and addressing potential bottlenecks.
+ Document changes, versioning, and standard processes
+ Strong communication skills and the ability to work effectively in a collaborative environment.
+ Excellent problem-solving and troubleshooting abilities, along with a strong analytical mentality and persistence in resolving problems.
+ Stay updated on emerging data engineering technologies and best practices.
Required Skills:
+ Bachelor's degree in computer science, data engineering, or a related field with 5 years experience (Master's preferred).
+ Proven experience in data engineering, ETL, and database management.
+ Proficiency in SQL and data manipulation languages.
+ Proven experience deploying solutions in Azure
+ Strong programming skills, with knowledge of languages like Python, Java, or Scala.
+ Strong understanding of fundamental data science concepts in NLP, including selection and understanding of embedding models.
+ Experience with data warehousing platforms (e.g., Amazon Redshift, Snowflake) and big data technologies (e.g., Hadoop, Spark).
+ Experience with database technologies for structured and unstructured data both for storage and optimal retrieval
+ Experience with highly scalable Data stores, Data Lake, Data Warehouse, Lakehouse, and unstructured datasets
+ Familiarity with data modeling and schema design.
+ Knowledge of data integration tools and data orchestration.
+ Excellent problem-solving and troubleshooting skills.
+ Strong communication and collaboration abilities.
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
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, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2023 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, 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 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.
Job Title: Senior Machine Learning Engineer
Job Location: Hybrid (preferred base cities - Atlanta, NYC, Dallas, Houston, Chicago, San Fran, and Seattle)
Job Description: As a Senior Machine Learning Engineer, you will lead the development and implementation of sophisticated data engineering solutions to support the deployment and optimization of AI models. Your role will involve demonstrating extensive experience to design robust, scalable, and innovative data architectures that align with the unique requirements of Artificial Intelligence applications.
Key Responsibilities:
+ The Machine Learning Engineer will be responsible for architectural design and planning, advanced data pipelines, model integration and optimization, scalability, performance and research and innovation supporting production AI systems.
+ Build and maintain data engineering solutions on cloud platforms using hyperscaler services (GPC, AWS, Azure).
+ Design, develop, and maintain data pipelines to efficiently collect, process, and load data from various sources into data storage systems (e.g., data warehouses, data lakes).
+ Develop and maintain data models and schema designs to support efficient data storage and retrieval.
+ Use hyperscaler technologies to support data needs for expansion of Machine Learning/Data Science capabilities including generative AI.
+ Implement data validation and data cleansing processes to ensure data quality and consistency.
+ Design, develop, and implement scalable data pipelines and ETL/ELT processes using Python, PySpark and API integrations.
+ Monitor ETL jobs, troubleshoot issues, and ensure data processing efficiency.
+ Administer and optimize databases, ensuring performance, scalability, and data security.
+ Collaborate with multi-functional teams to understand data requirements and integrate data into various applications and analytics platforms.
+ Collaborate with data scientists and analysts to understand data requirements and translate them into scalable, high performant data pipeline solutions.
+ Ensure compliance with data privacy and security regulations.
+ Optimize data systems for scalability and performance, anticipating and addressing potential bottlenecks.
+ Document changes, versioning, and standard processes
+ Strong communication skills and the ability to work effectively in a collaborative environment.
+ Excellent problem-solving and troubleshooting abilities, along with a strong analytical mentality and persistence in resolving problems.
+ Stay updated on emerging data engineering technologies and best practices.
Required Skills:
+ Bachelor's degree in computer science, data engineering, or a related field with 5 years experience (Master's preferred).
+ Proven experience in data engineering, ETL, and database management.
+ Proficiency in SQL and data manipulation languages.
+ Proven experience deploying solutions in Azure
+ Strong programming skills, with knowledge of languages like Python, Java, or Scala.
+ Strong understanding of fundamental data science concepts in NLP, including selection and understanding of embedding models.
+ Experience with data warehousing platforms (e.g., Amazon Redshift, Snowflake) and big data technologies (e.g., Hadoop, Spark).
+ Experience with database technologies for structured and unstructured data both for storage and optimal retrieval
+ Experience with highly scalable Data stores, Data Lake, Data Warehouse, Lakehouse, and unstructured datasets
+ Familiarity with data modeling and schema design.
+ Knowledge of data integration tools and data orchestration.
+ Excellent problem-solving and troubleshooting skills.
+ Strong communication and collaboration abilities.
Job: _Developer_
Organization: _I&D_
Title: _Machine Learning Engineer_
Location: _TX-Dallas_
Requisition ID: _075886_
Job Location: Hybrid (preferred base cities - Atlanta, NYC, Dallas, Houston, Chicago, San Fran, and Seattle)
Job Description: As a Senior Machine Learning Engineer, you will lead the development and implementation of sophisticated data engineering solutions to support the deployment and optimization of AI models. Your role will involve demonstrating extensive experience to design robust, scalable, and innovative data architectures that align with the unique requirements of Artificial Intelligence applications.
Key Responsibilities:
+ The Machine Learning Engineer will be responsible for architectural design and planning, advanced data pipelines, model integration and optimization, scalability, performance and research and innovation supporting production AI systems.
+ Build and maintain data engineering solutions on cloud platforms using hyperscaler services (GPC, AWS, Azure).
+ Design, develop, and maintain data pipelines to efficiently collect, process, and load data from various sources into data storage systems (e.g., data warehouses, data lakes).
+ Develop and maintain data models and schema designs to support efficient data storage and retrieval.
+ Use hyperscaler technologies to support data needs for expansion of Machine Learning/Data Science capabilities including generative AI.
+ Implement data validation and data cleansing processes to ensure data quality and consistency.
+ Design, develop, and implement scalable data pipelines and ETL/ELT processes using Python, PySpark and API integrations.
+ Monitor ETL jobs, troubleshoot issues, and ensure data processing efficiency.
+ Administer and optimize databases, ensuring performance, scalability, and data security.
+ Collaborate with multi-functional teams to understand data requirements and integrate data into various applications and analytics platforms.
+ Collaborate with data scientists and analysts to understand data requirements and translate them into scalable, high performant data pipeline solutions.
+ Ensure compliance with data privacy and security regulations.
+ Optimize data systems for scalability and performance, anticipating and addressing potential bottlenecks.
+ Document changes, versioning, and standard processes
+ Strong communication skills and the ability to work effectively in a collaborative environment.
+ Excellent problem-solving and troubleshooting abilities, along with a strong analytical mentality and persistence in resolving problems.
+ Stay updated on emerging data engineering technologies and best practices.
Required Skills:
+ Bachelor's degree in computer science, data engineering, or a related field with 5 years experience (Master's preferred).
+ Proven experience in data engineering, ETL, and database management.
+ Proficiency in SQL and data manipulation languages.
+ Proven experience deploying solutions in Azure
+ Strong programming skills, with knowledge of languages like Python, Java, or Scala.
+ Strong understanding of fundamental data science concepts in NLP, including selection and understanding of embedding models.
+ Experience with data warehousing platforms (e.g., Amazon Redshift, Snowflake) and big data technologies (e.g., Hadoop, Spark).
+ Experience with database technologies for structured and unstructured data both for storage and optimal retrieval
+ Experience with highly scalable Data stores, Data Lake, Data Warehouse, Lakehouse, and unstructured datasets
+ Familiarity with data modeling and schema design.
+ Knowledge of data integration tools and data orchestration.
+ Excellent problem-solving and troubleshooting skills.
+ Strong communication and collaboration abilities.
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
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, cloud and data, combined with its deep industry expertise and partner ecosystem. The Group reported 2023 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, 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 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.
Job Title: Senior Machine Learning Engineer
Job Location: Hybrid (preferred base cities - Atlanta, NYC, Dallas, Houston, Chicago, San Fran, and Seattle)
Job Description: As a Senior Machine Learning Engineer, you will lead the development and implementation of sophisticated data engineering solutions to support the deployment and optimization of AI models. Your role will involve demonstrating extensive experience to design robust, scalable, and innovative data architectures that align with the unique requirements of Artificial Intelligence applications.
Key Responsibilities:
+ The Machine Learning Engineer will be responsible for architectural design and planning, advanced data pipelines, model integration and optimization, scalability, performance and research and innovation supporting production AI systems.
+ Build and maintain data engineering solutions on cloud platforms using hyperscaler services (GPC, AWS, Azure).
+ Design, develop, and maintain data pipelines to efficiently collect, process, and load data from various sources into data storage systems (e.g., data warehouses, data lakes).
+ Develop and maintain data models and schema designs to support efficient data storage and retrieval.
+ Use hyperscaler technologies to support data needs for expansion of Machine Learning/Data Science capabilities including generative AI.
+ Implement data validation and data cleansing processes to ensure data quality and consistency.
+ Design, develop, and implement scalable data pipelines and ETL/ELT processes using Python, PySpark and API integrations.
+ Monitor ETL jobs, troubleshoot issues, and ensure data processing efficiency.
+ Administer and optimize databases, ensuring performance, scalability, and data security.
+ Collaborate with multi-functional teams to understand data requirements and integrate data into various applications and analytics platforms.
+ Collaborate with data scientists and analysts to understand data requirements and translate them into scalable, high performant data pipeline solutions.
+ Ensure compliance with data privacy and security regulations.
+ Optimize data systems for scalability and performance, anticipating and addressing potential bottlenecks.
+ Document changes, versioning, and standard processes
+ Strong communication skills and the ability to work effectively in a collaborative environment.
+ Excellent problem-solving and troubleshooting abilities, along with a strong analytical mentality and persistence in resolving problems.
+ Stay updated on emerging data engineering technologies and best practices.
Required Skills:
+ Bachelor's degree in computer science, data engineering, or a related field with 5 years experience (Master's preferred).
+ Proven experience in data engineering, ETL, and database management.
+ Proficiency in SQL and data manipulation languages.
+ Proven experience deploying solutions in Azure
+ Strong programming skills, with knowledge of languages like Python, Java, or Scala.
+ Strong understanding of fundamental data science concepts in NLP, including selection and understanding of embedding models.
+ Experience with data warehousing platforms (e.g., Amazon Redshift, Snowflake) and big data technologies (e.g., Hadoop, Spark).
+ Experience with database technologies for structured and unstructured data both for storage and optimal retrieval
+ Experience with highly scalable Data stores, Data Lake, Data Warehouse, Lakehouse, and unstructured datasets
+ Familiarity with data modeling and schema design.
+ Knowledge of data integration tools and data orchestration.
+ Excellent problem-solving and troubleshooting skills.
+ Strong communication and collaboration abilities.
Job: _Developer_
Organization: _I&D_
Title: _Machine Learning Engineer_
Location: _TX-Dallas_
Requisition ID: _075886_
Source : Capgemini