Machine Learning (ML) Engineer (US Hybrid)

DXC Technology - Philadelphia, PA

Full-time

Philadelphia, PA

Professional, Scientific, and Technical Services

About the position

The Machine Learning (ML) Engineer at DXC Technology is responsible for designing, building, and deploying machine learning models that are optimized for performance and scalability. This role involves collaboration with Data Scientists and Data Engineers to implement advanced ML solutions, ensuring that they meet business requirements and performance standards. The engineer will engage directly with customers to understand their needs and deliver tailored ML projects, utilizing deep learning frameworks and cloud-native solutions, particularly on AWS.

Responsibilities

• Design, build, and deploy machine learning models within the proposed platform, ensuring they are optimized for performance and scalability.
• Collaborate with Data Scientists and Data Engineers to implement feature stores, model management (MLOps), and Explainable AI (XAI) capabilities.
• Monitor and optimize the performance of deployed models, ensuring they meet business requirements and performance standards.
• Support model management, versioning, and deployment workflows to streamline the operationalization of machine learning models.
• Engage directly with customers to understand their business problems and help implement tailored ML solutions.
• Deliver Machine Learning projects end-to-end, including understanding business needs, planning projects, aggregating & exploring data, building & validating predictive models, and deploying completed ML capabilities on the AWS Cloud to deliver business impact.
• Utilize deep learning frameworks like PyTorch and TensorFlow to build computer vision models for versatile applications.
• Work on large-scale datasets, creating scalable, robust, and accurate computer vision systems.
• Collaborate with Cloud Architects to build secure, robust, and easy-to-deploy cloud-native machine learning solutions.
• Work closely with customer account teams and product engineering teams to optimize model implementations and deploy cutting-edge algorithms.
• Assist customers with Machine Learning Operations (MLOps) workflows such as model deployment, retraining, testing, and performance monitoring.

Requirements

• Bachelor's degree in a relevant field or equivalent combination of education and experience.
• Typically, 7+ years of relevant work experience in industry, with a minimum of 3 years in a similar role.
• Proven experience in data architecture and management.
• Proficiencies in data modeling, data warehousing, ETL processes, and database technologies.
• Continuous learner that stays abreast with industry knowledge and technology.

Nice-to-haves

• Proven experience in building and deploying machine learning models at scale.
• Proficiency with deep learning frameworks like PyTorch and TensorFlow.
• Experience with cloud-native machine learning solutions, preferably on AWS.
• Experience with Databricks.
• Experience with Agile Methodology.
• Strong understanding of MLOps workflows, including model management.
• Ability to work independently and collaboratively with cross-functional teams.