Performance Management Engineer

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. Your Role As a

Machine Learning Engineer at Capgemini

, you will play a critical role in the development, integration, enhancement, and optimization of machine learning solutions that support business decision-making and operational excellence. You will collaborate closely with data scientists, business stakeholders, and subject matter experts (SMEs) to translate business requirements into scalable technical solutions. This role requires strong Python programming skills, machine learning expertise, cloud experience in Google Cloud Platform (GCP), and the ability to work independently in a fast-paced, data-driven environment.

Responsibilities & Scope Develop, enhance, and maintain machine learning solutions and predictive analytics models. Support the integration, deployment, monitoring, and upgrading of ML models in production environments. Translate business requirements into actionable technical solutions and implementation plans. Collaborate with SMEs and business stakeholders to understand operational processes and technical requirements. Develop and optimize data processing workflows using Python, SQL, Pandas, and NumPy. Build and maintain data visualizations and reporting solutions using

Bokeh

. Ensure data quality, reliability, and consistency throughout the machine learning lifecycle. Manage source code and collaborative development processes using

Git

. Participate in testing, validation, and quality assurance activities related to data and machine learning solutions. Support troubleshooting, performance optimization, and enhancement of deployed analytics applications. Document technical solutions, development processes, and best practices. Work effectively both independently and within Agile delivery teams.

Your Profile Innovation-driven professional

• Passionate about data, analytics, and machine learning technologies. Strong problem solver
• Able to break down complex business problems into practical technical solutions. Independent contributor
• Comfortable working with minimal supervision while managing priorities effectively. Collaborative team player
• Works effectively with technical teams, business stakeholders, and domain experts. Analytical thinker
• Skilled at interpreting data and identifying opportunities for optimization. Continuous learner
• Eager to expand expertise in machine learning, cloud, and MLOps technologies.

Qualifications & Preferred Skills Required Qualifications Bachelor's Degree in a STEM field (Science, Technology, Engineering, Mathematics, or related discipline). Experience supporting machine learning projects within enterprise environments. Advanced English communication skills. Required Skills Strong proficiency in

Python programming

with experience supporting machine learning solutions. Experience updating, maintaining, and integrating

Machine Learning models

. Hands-on experience working with

Google Cloud Platform (GCP)

. Strong understanding of machine learning concepts and model lifecycle management. Experience with

SQL querying

and data analysis. Proficiency with

Pandas

and

NumPy

. Experience using

Git

and version control best practices. Knowledge of software testing and

Quality Assurance

principles. Ability to translate business requirements into technical deliverables. Experience collaborating with Subject Matter Experts (SMEs) and business stakeholders. Strong analytical, troubleshooting, and communication skills. Ability to work independently and manage multiple priorities. Experience building data visualizations using

Bokeh

. Preferred Skills Experience with

Data Modeling

and

ETL processes

. Experience delivering projects using

Agile/Scrum methodologies

. Knowledge of

Dataiku

. Understanding of

performance optimization, monitoring, profiling, and scaling strategies

. Familiarity with

signal processing concepts

. Engineering background. Experience within the

Oil & Gas / Oilfield domain

, including industry terminology and business processes. Growth & Development Opportunities The following areas will be supported through training and enablement programs: CI/CD Pipelines and DevOps practices. MLOps and model deployment best practices. Prognostics & Health Management (PHM) techniq