Machine Learning Engineering Intern jobs at Paypal in France

Essential Responsibilities:

• Define and lead the learning and development strategy for key business functions, ensuring alignment with business goals and the long-term development roadmap.
• Ensure the design, architecture, and execution of large-scale learning programs, establishing metrics and evaluation processes to assess effectiveness and drive continuous improvement based on data-driven decisions.
• Collaborate with senior business leaders and cross-functional teams to assess learning needs, create targeted solutions, and ensure the scalability and effectiveness of learning programs.
• Provide thought leadership and mentorship to Learning & Development team members, fostering an innovative and collaborative team culture that drives performance and achieves outcomes.
• Leverage insights from market best practices, emerging trends, and industry benchmarks to influence long-term learning strategy, ensuring the organization is competitive and responsive to future learning needs.
• Oversee the budget and resource allocation for learning programs, manage relationships with external vendors, and ensure cost-effective procurement of learning resources, tools, and technologies while maintaining alignment with business priorities.

Expected Qualifications:

• 10+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.

• 10+ years relevant experience and a bachelor’s degree OR Any equivalent combination of education and experience.
• Experience in learning & development, technology training, or related fields.
• Bachelor’s degree in a relevant discipline, or equivalent combination of education and experience.
• Proven success designing and delivering large-scale learning programs for technical audiences.
• Strong ability to partner with executives and cross-functional teams to align learning with strategic priorities.
• Deep understanding of developer workflows, modern engineering practices, and emerging tools.
• Exceptional communication, leadership, and change management skills

Travel Percent:

The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit .

The US national annual pay range for this role is $123,500 to $212,850

Our Benefits:

Any general requests for consideration of your skills, please

Essential Responsibilities:

• Develop and optimize machine learning models for various applications.
• Preprocess and analyze large datasets to extract meaningful insights.
• Deploy ML solutions into production environments using appropriate tools and frameworks.
• Collaborate with cross-functional teams to integrate ML models into products and services.
• Monitor and evaluate the performance of deployed models.

Expected Qualifications:

• 3+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.
• Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
• Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
• Several years of experience in designing, implementing, and deploying machine learning models.

• Advanced degree (Master's or Ph.D.) in a quantitative discipline such as Statistics, Mathematics, Computer Science, Engineering, or a related field.
• Strong knowledge of statistical and machine learning techniques, including but not limited to logistic regression, time-series modeling, random forests, support vector machines, gradient boosting (e.g., XGBoost), and deep learning architectures (e.g., CNNs, RNNs).
• Proficiency in programming and big-data technologies, with hands-on experience in tools such as Python (Scikit-learn, TensorFlow), SQL, Hadoop, and Spark.
• Relevant modeling experience in one or more of the following domains: credit risk scoring, fraud detection, financial forecasting, or marketing analytics - gained through industry or academic research.
• Strong collaboration and communication skills, with the ability to work effectively both independently and as part of a cross-functional team.
• Ability to articulate complex technical concepts clearly to non-technical stakeholders and build constructive working relationships across functions.

Preferred Qualifications

• Experience with Large Language Models (LLMs), Agentic AI, or related generative AI applications.
• Familiarity with model governance, model risk management, or AI regulatory compliance frameworks (e.g., SR 11-7, OCC 2011-12, EU AI Act) is a plus.

Travel Percent:

The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit .

The US national annual pay range for this role is $137,500 to $236,500

Belonging at PayPal:

Any general requests for consideration of your skills, please

This job will lead the design, development, and implementation of advanced machine learning models and algorithms to solve complex problems. You will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences.

Essential Responsibilities:

• Lead the development and optimization of advanced machine learning models.
• Oversee the preprocessing and analysis of large datasets.
• Deploy and maintain ML solutions in production environments.
• Collaborate with cross-functional teams to integrate ML models into products and services.
• Monitor and evaluate the performance of deployed models, making necessary adjustments.

Minimum Qualifications:

• Minimum of 8 years of relevant work experience and a Bachelor's degree or equivalent experience.
• Extensive experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
• Expertise in cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.

Our Benefits:

Any general requests for consideration of your skills, please

Essential Responsibilities:

• Directs and controls the delivery of business and technical outcomes that comprise multiple projects and operational activities within a domain through organizational and technical leadership
• Defines engineering health objectives that drive organization health, engineering best practices and operational targets
• Drives product and technical strategy with cross-functional leaders across the enterprise to deliver Domain goals
• Responsible for the delivery of programs, establishing annual organizational goals and ensuring performance and results that impact both their domain and potentially enterprise
• Develops engineering strategy that translates into operational and tactical plans; uses ground-breaking methods to think beyond existing solutions
• Sets the tri-annual roadmap for a domain level organization. Defines the operational strategy for a domain based on a defined budget
• Evaluates key business challenges and can complete complex, ambiguous initiatives having impact across engineering; directs the development of new or innovative solutions. Ability to deal with high levels of technical domain level ambiguity.
• Collaborates with direct team, managers in org, stakeholders, managers in other orgs, external partners and business stakeholders

Expected Qualifications:

• Minimum of 15 years of relevant work experience and a Bachelor's degree or equivalent experience.
• Minimum of 3 years management experience

• Deep knowledge of distributed systems design, full-stack application development, RESTful services, Mobile and cloud computing technologies
• Success in partnering with cross-functional teams to deliver global-class products in highly dynamic environments.'
• Ability to balance business priorities and technical rigor within fast-paced delivery cycles.
• Cloud migration

Travel Percent:

The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit .

The US national annual pay range for this role is $188,000 to $323,950

Our Benefits:

Any general requests for consideration of your skills, please

• Strong proficiency in Python for data analysis, machine learning, and automation.
• Solid understanding of supervised and unsupervised AI/machine learning methods (e.g., XGBoost, LightGBM, Random Forest, clustering, isolation forests, autoencoders, neural networks, transformer-based architectures).
• Experience in payment fraud, AML, KYC, or broader risk modeling within fintech or financial institutions.
• Experience developing and deploying ML models in production using frameworks such as scikit-learn, TensorFlow, PyTorch, or similar.
• Hands-on experience with LLMs (e.g., OpenAI, LLaMA, Claude, Mistral), including use of prompt engineering, retrieval-augmented generation (RAG), and agentic AI to support internal automation and risk workflows.
• Ability to work cross-functionally with engineering, product, compliance, and operations teams.

Essential Responsibilities:

• Develop and optimize machine learning models for various applications.
• Preprocess and analyze large datasets to extract meaningful insights.
• Deploy ML solutions into production environments using appropriate tools and frameworks.
• Collaborate with cross-functional teams to integrate ML models into products and services.
• Monitor and evaluate the performance of deployed models.

Minimum Qualifications:

• Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent experience.
• Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
• Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
• Several years of experience in designing, implementing, and deploying machine learning models.

Our Benefits:

Any general requests for consideration of your skills, please

This job will design, develop, and implement machine learning models and algorithms to solve complex problems. You will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences.

Essential Responsibilities:

• Develop and optimize machine learning models for various applications.
• Preprocess and analyze large datasets to extract meaningful insights.
• Deploy ML solutions into production environments using appropriate tools and frameworks.
• Collaborate with cross-functional teams to integrate ML models into products and services.
• Monitor and evaluate the performance of deployed models.

Minimum Qualifications:

• Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent experience.
• Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
• Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
• Several years of experience in designing, implementing, and deploying machine learning models.

Preferred Qualification:

Our Benefits:

Any general requests for consideration of your skills, please

This job will design, develop, and implement machine learning models and algorithms to solve complex problems. You will work closely with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. Your role will involve building scalable ML pipelines, ensuring data quality, and deploying models into production environments to drive business insights and improve customer experiences.

Essential Responsibilities:

• Develop and optimize machine learning models for various applications.
• Preprocess and analyze large datasets to extract meaningful insights.
• Deploy ML solutions into production environments using appropriate tools and frameworks.
• Collaborate with cross-functional teams to integrate ML models into products and services.
• Monitor and evaluate the performance of deployed models.

Minimum Qualifications:

• Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent experience.
• Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
• Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment.
• Several years of experience in designing, implementing, and deploying machine learning models.

Preferred Qualification:

Responsibilities:

• Write clean, high-performance, high-quality, maintainable code
• Discovering, analyzing, structuring and mining data
• Be a key engineer contributing to the design, development of the new ML and Gen AI based solutions, improving and maintaining the same.
• Work with data scientists and backend engineers to implement scalable AI and ML solutions to solve complex problems.
• Maintain and enhance the existing architectural documentations and create the new one as needed
• Highly effective at working in cross-functional groups and getting results in matrix organizations
• Highly analytical, innovative, and able to think strategically and to develop comprehensive detailed specifications
Qualifications and skills:

• B.S./B.E/B.Tech in computer sciences with 5+ years of experience or equivalent
• Experience in building production grade Gen AI applications including Prompt Engineering and RAG fine-tuning techniques and usage of Agentic frameworks like Langraph, Langchain, CrewAI etc.
• Experience in Fine Tuning LLMs is a plus
• Experience with cloud technologies (GCP/AWS/Azure.) is recommended.
• Experience on building shallow learning and deep learning applications, using TensorFlow, PyTorch, H2O, SciKit-Learn, Keras, Spark MLlib, XGBoost, LightGBM etc.
• ML Design pattern, algorithm and the data structure skills
• Worked in development environments following agile principles and methodology
• Experience in working with GPU, profiling/low-level optimizations, Cuda/CuDNN is a plus
• Experience with one or more Container-ecosystem (Docker, Mesos, Kubernetes) is a plus
• Experience with Big Data Platform and data processing frameworks (Hadoop, Hive, Map Reduce, Spark, etc.) and professional skill in writing optimal production grade SQL queries is a plus
• Experience on data mining, feature engineering, and distributed data programming
• Excellent communication skill to global business and technical partners
• Highly motivated, goal driven, can-do attitude
• Innovative, entrepreneurial, team player, ability to multi-task
• Flexible in learning new tools and technologies and quickly on boarding solutions using solutions using them.

Our Benefits:

Any general requests for consideration of your skills, please