Machine Learning (ML) Engineer - HP Digital Products Team

HP•Houston, TX

About The Position

Machine Learning (ML) Engineer - HP Digital Products Team Description - HP is the world’s leading personal systems and printing company, we create technology that makes life better for everyone, everywhere. Our innovation springs from a team of individuals, each collaborating and contributing their own perspectives, knowledge, and experience to advance the way the world works and lives. We are looking for visionaries, like you, who are ready to make a purposeful impact on the way the world works. At HP, the future is yours to create! The Digital Products team is responsible for the design, build, and deployment of world class AI enabled products and solutions that empower a future ready workforce, drive efficiencies via automation and support implementation of newer business operating models for HP’s business. With a focus on Innovation, the group drives differentiation with architectural vision to consolidate, accelerate and simplify new technology adoption and deliver high value solutions that solve the pain points of all its stakeholders. Role Overview: We are seeking a Machine Learning Engineer to design, develop, and deploy AI/ML models that power innovative digital products. You will collaborate closely with AI Solutions Architects, Domain Solution Architects, Full Stack Engineers, and Product teams to ensure models are production-ready, scalable, and aligned with business objectives.

Requirements

Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or related field.
3–7 years of experience in ML/AI engineering, including model development and deployment.
Proficiency in Python, R, or similar languages, and ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
Experience with cloud platforms (AWS, Azure, GCP) and ML deployment pipelines (MLOps).
Strong knowledge of data preprocessing, feature engineering, and model evaluation techniques.
Ability to work in cross-functional agile teams and communicate technical concepts effectively.

Nice To Haves

Experience in deploying ML models in production at scale.
Familiarity with containerization (Docker/Kubernetes) and microservices for ML applications.
Prior experience in product-focused or squad-based digital engineering teams.
Knowledge of domain-specific applications of AI (healthcare, finance, retail, etc.).

Responsibilities

Design, implement, and optimize ML models for production systems, ensuring accuracy, efficiency, and scalability.
Collaborate with Full Stack Engineers and AI Solutions Architects to integrate ML models into applications and platforms.
Develop and maintain data pipelines and workflows to support training, testing, and deployment of ML models.
Evaluate and implement state-of-the-art ML algorithms and frameworks suitable for domain-specific problems.
Monitor, troubleshoot, and improve model performance in production.
Work with Product Managers and Data Analysts to translate business requirements into ML solutions.
Contribute to architecture discussions, best practices, and reusable ML frameworks across the organization.
Stay up-to-date with emerging trends and technologies in AI and ML to bring innovation into production solutions.

Benefits

Health insurance
Dental insurance
Vision insurance
Long term/short term disability insurance
Employee assistance program
Flexible spending account
Life insurance
Generous time off policies, including; 4-12 weeks fully paid parental leave based on tenure
11 paid holidays
Additional flexible paid vacation and sick leave