ML Web Architect: Build Scalable AI Apps on AWS

Bloomberg Industry Group; Virginia (MN); On-site; USD 110,000 - 140,000; Full time

Job summary

Bloomberg Industry Group in Arlington, VA seeks a Machine Learning Engineer to innovate and deliver AI/ML solutions within the ML team. You will develop, integrate, deliver, and support ML solutions, collaborating across teams and ensuring production-ready code.

Responsibilities include implementing ML solutions with AWS, shaping project architecture, building scalable pipelines, and applying DevOps practices.

Qualifications

• Bachelor's degree in mathematics, statistics, computer science or a related STEM field; Master’s degree preferred.
• 1+ years of software development and/or ML application experience.
• Proficiency with an object-oriented language such as Java or Python and ML/AI libraries.
• Knowledge of software engineering practices across the SDLC, including testing and CI/CD.

Responsibilities

• Implement ML-based solutions addressing business challenges while aligning with INDG practices and AWS integration.
• Collaborate with cross-functional teams to gather requirements and shape project architecture with cloud considerations.
• Architect and implement scalable ML pipelines and infrastructure using AWS and DevOps practices.
• Build enterprise applications at scale with strong CS fundamentals.
• Use data-driven metrics to guide decisions and diagnose production issues.
• Write and maintain production-quality code and contribute to special projects.

Skills

Java

Python

ML/AI frameworks

Cloud computing

Education

Bachelor's degree in STEM

Master's degree in STEM

Tools

AWS

DevOps practices

Git

Job description

Bloomberg Industry Group in Arlington, VA seeks a Machine Learning Engineer to innovate and deliver AI/ML solutions within the ML team. You will develop, integrate, deliver, and support ML solutions, collaborating across teams and ensuring production-ready code.

Responsibilities include implementing ML solutions with AWS, shaping project architecture, building scalable pipelines, and applying DevOps practices.