Machine Learning Engineer

2 months ago

Reading, Berkshire, United Kingdom Hewlett-Packard Full time

HP is a Fortune 100 technology company with $58+ Billion in revenue, with over 50,000 employees operating in more than 170 countries around the world. We provide technology and services that help people and companies address their problems and challenges, and realize their possibilities, aspirations and dreams. We apply new thinking and ideas to create simpler, more valuable and trusted experiences with technology, continuously improving the way our customers live and work.

Position Background:

Join the global team at HP Inc., where we are revolutionizing pricing strategies for thousands of products worldwide every day using state-of-the-art machine learning, data science, and econometrics. As a leader in technology, HP is committed to innovation, and our pricing analytics team is at the forefront, driving value and efficiency across our global operations.

We are looking for a passionate and skilled Machine Learning Engineer to join our dynamic global pricing analytics team. In this role, you will be responsible for the development, deployment, and monitoring of advanced machine learning models that directly impact HP’s pricing strategies. You will work closely with a talented team of data scientists while also collaborating with data engineering and ML platform teams to ensure our models are robust, scalable, and optimized for performance.

What we offer:

• Your work will directly shape pricing strategies that drive business outcomes, influencing HP’s sales and strategic decisions worldwide, with a tangible impact on the company’s global success

• Collaborate with a global team that values innovation, creativity, and continuous learning across different locations and nationalities, making a worldwide impact on HPs global operations

• At HP, we’re committed to fostering an environment where you can continuously advance your skills and career, with access to structured growth opportunities, including career progression plans, training days, and a wide range of internal and external learning resources

• Hybrid work environment that combines in-office collaboration and in-person dynamics with remote work flexibility, allowing you to balance focused productivity with personal well-being

Responsibilities:

• Model Development: Collaborate with data scientists to translate machine learning prototypes into production-ready models. Implement, test, and refine ML-based algorithms to meet business needs, ensuring high performance while maintaining scalability

• Deployment and Monitoring: Deploy machine learning models into production environments, ensuring they are scalable, efficient, and seamlessly integrated with existing systems. Monitor model performance in real-time, making adjustments with the team as necessary

• Automation and Scalability: Customize the automated CI/CD pipelines for model training, evaluation, and deployment provided by the central ML platform team to meet the needs of the pricing team. Work on scaling solutions to handle large datasets and increasing demand across global operations

• Performance Optimization: Continuously optimize the performance of ML solutions, focusing on reducing latency, resource usage, and improving overall efficiency

• Collaboration: Work closely with the data science team, data engineering team, and ML platform team to ensure smooth integration and operation of machine learning models. Provide technical expertise and guidance on best practices for model development and deployment. Influence the long-term evolution of our ML platform

Job Requirements:

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field

• At least 3 years of professional experience in machine-learning models development and deployment. Experience in monitoring and supporting production models at scale

• Strong programming skills in Python, along with experience in ML/DS libraries and frameworks (e.g., scikit-learn, pandas, polars). Knowledge of C++ is a plus

• Experience with Docker and in creating, managing, and optimizing Docker containers.

• Proficiency in Test-Driven-Development (TDD), integration testing, unit testing and be able to ensure quality code at delivery time, such as review Pull-Requests in a standardized manner.

• Experience with artifact stores and model management tools (e.g., MLflow, DVC) for managing and versioning machine learning models

• CI/CD Expertise using GitHub Actions: Hands-on experience in setting up and managing continuous integration/continuous deployment (CI/CD) pipelines using GitHub Actions

• Collaborative Development: Ability to work in a collaborative environment, using Docker and GitHub to facilitate smooth integration and deployment processes across development teams

• Experience with cloud platforms, specific knowledge of AWS is a plus.

• Documentation and Best Practices: Strong ability to document processes, workflows, and best practices for Python and CI/CD pipeline management.

• Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment

• Strong English communication skills, with the ability to convey complex technical concepts to both technical and non-technical stakeholders

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