Machine Learning Engineer
hace 4 semanas
HP is a global technology leader with a commitment to innovation. Our pricing analytics team is at the forefront of driving value and efficiency across our operations. We're seeking a skilled Machine Learning Engineer to join our dynamic team and contribute to the development, deployment, and monitoring of advanced machine learning models that directly impact our pricing strategies.
Key Responsibilities:- 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.
- 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.
- Customize 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.
- Continuously optimize the performance of ML solutions, focusing on reducing latency, resource usage, and improving overall efficiency.
- 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 ensuring quality code at delivery time.
- 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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