Machine Learning Ops Solution Architect

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.

We are seeking an experienced and innovative MLOps Solution Architect to join our dynamic team. With over a decade of expertise in AI/ML model development and deployment, you will play a critical role in designing and implementing end-to-end data-driven solutions. If you're passionate about leveraging cutting-edge technologies to solve complex challenges, we want to hear from you!

Key Responsibilities

Solution Design and Implementation

Architect and deploy data-driven solutions using advanced machine learning, deep learning, and MLOps frameworks.

Conceptualize and implement Generative AI solutions tailored to business needs.

Develop models for text analytics, language processing, document similarity, and classification using techniques like latent semantic analysis and neural networks.

Build recommender systems employing content-based and collaborative filtering approaches.

Drive computer vision solutions leveraging Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs).

Model Lifecycle Management

Implement robust MLOps processes for model validation, explainability, monitoring, and management using frameworks like AI Glass Box.

Ensure scalability and reliability in model deployment pipelines using modern best practices.

Statistical Analysis and Predictive Modeling

Apply statistical techniques for predictive analytics and statistical modeling to address business challenges effectively.

Collaboration and Leadership

Partner with cross-functional teams to translate business requirements into technical solutions.

Mentor junior data scientists and engineers to foster a culture of continuous learning and innovation.

Qualifications and Skills

Required Experience

10+ years of experience in AI/ML model development and deployment.

3+ years of experience as a Solution Architect, designing scalable AI/ML solutions.

Proficiency in supervised and unsupervised machine learning and deep learning algorithms.

Expertise in MLOps, including model validation, explainability, and monitoring.

Hands-on experience in Generative AI solutions.

Technical Proficiencies

Programming: Python, SQL.

Frameworks and Tools: TensorFlow, Keras, PySpark, Hive, NLTK.

MLOps: Model monitoring and explainability frameworks like AI Glass Box.

Cloud and DevOps: Experience with Azure DevOps (ADO) and related tools.

Preferred Skills

Experience with statistical modeling and predictive analytics.

Strong expertise in natural language processing (NLP) and text analytics.

Familiarity with recommender systems and advanced image analytics.

Core Competencies

Problem Solving: Strong analytical skills to tackle complex business challenges.

Collaboration: Proven ability to work in multidisciplinary teams, fostering innovation.

Continuous Learning: Enthusiasm for keeping up with the latest advancements in AI/ML and MLOps.

Leadership: Experience in mentoring teams and contributing to strategic decision-making.

WHAT YOU'LL LOVE ABOUT WORKING HERE

We promote Diversity & Inclusion as we believe diversity of thought fuels excellence and innovation.

In Capgemini, you are the architect of your career growth. We equip people in maximizing their full potential by providing wide array of career growth programs that empower them to get the future they want.

Capgemini fosters impactful experiences for its people that would aid in bringing out the best in them for them, for the company, and for their clients.

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, 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

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.

We are seeking an experienced and innovative MLOps Solution Architect to join our dynamic team. With over a decade of expertise in AI/ML model development and deployment, you will play a critical role in designing and implementing end-to-end data-driven solutions. If you're passionate about leveraging cutting-edge technologies to solve complex challenges, we want to hear from you!

Key Responsibilities

Solution Design and Implementation

Architect and deploy data-driven solutions using advanced machine learning, deep learning, and MLOps frameworks.

Conceptualize and implement Generative AI solutions tailored to business needs.

Develop models for text analytics, language processing, document similarity, and classification using techniques like latent semantic analysis and neural networks.

Build recommender systems employing content-based and collaborative filtering approaches.

Drive computer vision solutions leveraging Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs).

Model Lifecycle Management

Implement robust MLOps processes for model validation, explainability, monitoring, and management using frameworks like AI Glass Box.

Ensure scalability and reliability in model deployment pipelines using modern best practices.

Statistical Analysis and Predictive Modeling

Apply statistical techniques for predictive analytics and statistical modeling to address business challenges effectively.

Collaboration and Leadership

Partner with cross-functional teams to translate business requirements into technical solutions.

Mentor junior data scientists and engineers to foster a culture of continuous learning and innovation.

Qualifications and Skills

Required Experience

10+ years of experience in AI/ML model development and deployment.

3+ years of experience as a Solution Architect, designing scalable AI/ML solutions.

Proficiency in supervised and unsupervised machine learning and deep learning algorithms.

Expertise in MLOps, including model validation, explainability, and monitoring.

Hands-on experience in Generative AI solutions.

Technical Proficiencies

Programming: Python, SQL.

Frameworks and Tools: TensorFlow, Keras, PySpark, Hive, NLTK.

MLOps: Model monitoring and explainability frameworks like AI Glass Box.

Cloud and DevOps: Experience with Azure DevOps (ADO) and related tools.

Preferred Skills

Experience with statistical modeling and predictive analytics.

Strong expertise in natural language processing (NLP) and text analytics.

Familiarity with recommender systems and advanced image analytics.

Core Competencies

Problem Solving: Strong analytical skills to tackle complex business challenges.

Collaboration: Proven ability to work in multidisciplinary teams, fostering innovation.

Continuous Learning: Enthusiasm for keeping up with the latest advancements in AI/ML and MLOps.

Leadership: Experience in mentoring teams and contributing to strategic decision-making.

WHAT YOU'LL LOVE ABOUT WORKING HERE

We promote Diversity & Inclusion as we believe diversity of thought fuels excellence and innovation.

In Capgemini, you are the architect of your career growth. We equip people in maximizing their full potential by providing wide array of career growth programs that empower them to get the future they want.

Capgemini fosters impactful experiences for its people that would aid in bringing out the best in them for them, for the company, and for their clients.

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, 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