Machine Learning (ML) Engineer (US Hybrid)i

Job Description:

DXC Technology (NYSE: DXC) helps global companies run their mission-critical systems and operations while modernizing IT, optimizing data architectures, and ensuring security and scalability across public, private, and hybrid clouds. The world’s largest companies and public sector organizations trust DXC to deploy services across the Enterprise Technology Stack to drive new performance levels, competitiveness, and customer experience. Learn more about how we deliver excellence for our customers and colleagues at DXC.com.

Essential Job Functions
• 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.
• Apply best practices from core Software Development activities to Machine Learning, including deplorability, unit testing, and structured, extensible software development.

Basic Qualifications
• 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

Other Qualifications
• 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.

Work Environment:
• Must be legally authorized to work in the United stated without requiring sponsorship now or in the future
• Our client falls under the International Traffic in Arms Regulations (ITAR) and must comply with the ITAR, which mandates that all applicants hold US person.

If you are an applicant from the United States, Guam, or Puerto Rico

DXC Technology is an Equal Opportunity/Affirmative Action employer. All qualified candidates will receive consideration for employment without regard to disability, protected veteran status, race, color, religious creed, national origin, citizenship, marital status, sex, ****** orientation/gender identity, age or genetic information. DXC's commitment to diversity and inclusive selection practices includes ensuring qualified long-term unemployed job seekers receive equal consideration for employment. View postings below.

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