Senior Machine Learning Engineer

For more than 20 years, our global network of passionate technologists and pioneering craftspeople has delivered cutting-edge technology and game-changing consulting to companies on the brink of AI-driven digital transformation. Since 2001, we have grown into a full-service digital consulting company with 5500+ professionals working on a worldwide ambition.

Driven by the desire to make a difference, we keep innovating. Fueling the growth of our company with our knowledge worker culture. When teaming up with Xebia, expect in-depth expertise based on an authentic, value-led, and high-quality way of working that inspires all we do.

About the Role

As a Senior Machine Learning Engineer, you will operationalize innovative ML solutions and work alongside other team members like product manager, Enterprise architect, Principal ML Engineer, Data scientists and business to design, build ML pipeline and productionalize ML models. You will be also responsible for integrating ML solutions to operational products. This hands-on technical role demands excellent ML engineering and MLops knowledge and can demonstrate best practices in the industry. Come be a part of a team that is starting this new journey.

We are looking for someone who is a technology-agnostic polymath—committed to a lifelong journey of learning and exploration of new scientific ideas—and will bring thoughtful perspectives, empathy, creativity, and a positive attitude to solve problems at scale. This role is ideal for someone looking to extend their machine learning and software engineering skills to lead ML engineering team and create impact by delivering ML capabilities at scale

What You’ll Do

• Responsible for executing ML operationalization across enterprise.
• Architect, build, maintain, and improve end to end ML systems.
• Implement end-to-end solutions for batch and real-time algorithms along with tooling around monitoring, logging, automated testing, performance testing and A/B testing.
• Collaborate with Product, Engineering , Data scientists and Business teams on planning new capabilities.
• Establish scalable, efficient, automated processes for data analyses, model development, validation and implementation.
• Write efficient and well-organized software to ship products in an iterative, continual-release environment.

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• Actively participate in code review and test solutions to ensure it meets best practice specifications.
• Contribute to and promote good software engineering practices across the team.
• Excellent communication skills, with the ability to explain complex technical concepts to technical and non-technical audiences.
• Demonstrate our values of Passion for Client Service, Innovation, Expertise, Balance, Respect for All, Teamwork, and Initiative.
• Support technical evaluations of other consultants when required, contributing to the assessment of skills and alignment with project needs

What You Bring

• University or advanced degree in engineering, computer science, mathematics, or a related field.
• 2+ years of experience developing and deploying machine learning systems into production.
• 5+ years of experience in Software engineering space.
• Experience working with a variety of relational SQL and NoSQL databases.
• Experience working with: Hadoop, Spark, Kafka, Scala, Python, R etc.
• Knowledge of cloud platforms (Azure, AWS or equivalent cloud platforms)
• Microsoft Azure: Experience designing, deploying, and administering scalable, available, and fault tolerant systems on Microsoft Azure using HDInsights or Analytics Platform System (APS)
• Experience with Azure Management Portal, Azure Machine Learning, and Azure SQL Server
• Hadoop: Experience with storing, joining, filtering, and analyzing data using Spark, Hive and Map Reduce
• Hands-on Experience working with Databricks.

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• Hands-on Experience working with Claude.
• Experience with deep learning frameworks such as PyTorch, TensorFlow, Keras or similar
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala, etc.
• Industry experiences building and productionizing creative end-to-end Machine Learning systems
• Experience with building and operationalize feature store.
• Experience working with distributed systems, service oriented architectures and designing APIs/ API Graph.
• Familiarity in deploying real-time ML systems on Azure Cloud through frameworks such as ONNX, MLEAP , TF Serving etc.
• Experience using opensource LLMs, LLMOPs.
• Knowledge of data pipeline and workflow management tools
• Expertise in standard software engineering methodology, e.g. unit testing, test automation, continuous integration, code reviews, design documentation
• Relevant working experience with Kubernetes.

What We Offer

• 100% remote work to provide flexibility and work-life balance.
• Company laptop and necessary equipment to perform your role effectively.
• Competitive salary package aligned with local market benchmarks.

Xebia is committed to creating an inclusive and diverse environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability or age.