Machine Learning Engineer , Data & Machine Learning (dml)

Amazon Amazon · Big Tech · Arlington, VA · Applied Science

Machine Learning Engineer to join AWS Professional Services (ProServe) team. The role involves designing, implementing, and scaling AI/ML solutions for customers, applying Generative AI algorithms to solve real-world problems, and providing expertise throughout the project lifecycle. Responsibilities include architecting solutions, selecting and fine-tuning models, developing proof-of-concepts, running experiments, and providing technical guidance on responsible AI usage.

What you'd actually do

  1. Designing and implementing complex, scalable, and secure AI/ML solutions on AWS tailored to customer needs, including selecting and fine-tuning appropriate models for specific use cases
  2. Developing and deploying machine learning models and generative AI applications that solve real-world business problems, conducting experiments and optimizing for performance at scale
  3. Collaborating with customer stakeholders to identify high-value AI/ML use cases, gather requirements, and propose effective strategies for implementing machine learning and generative AI solutions
  4. Providing technical guidance on applying AI, machine learning, and generative AI responsibly and cost-efficiently, troubleshooting throughout project delivery and ensuring adherence to best practices
  5. Acting as a trusted advisor to customers on the latest advancements in AI/ML, emerging technologies, and innovative approaches to leveraging diverse data sources for maximum business impact
  6. Sharing knowledge within the organization through mentoring, training, creating reusable AI/ML artifacts, and working with team members to prototype new technologies and evaluate technical feasibility

Skills

Required

  • Bachelor's degree or above in Science, Technology, Engineering, or Mathematics (STEM)
  • Experience in professional software engineering & best practices for the full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques
  • Current, active US Government Security Clearance of Top Secret or above

Nice to have

  • Master's degree or above in Science, Technology, Engineering, or Mathematics (STEM)
  • Experience working on multi-team, cross-disciplinary projects
  • Experience applying quantitative analysis to solve business problems and making data-driven business decisions
  • Experience in defining and creating benchmarks for assessing GenAI model performance

What the JD emphasized

  • US Citizen and currently possess and maintain an active Top Secret security clearance
  • must currently possess and maintain an active TS/SCI security clearance

Other signals

  • design, evangelize, implement, and scale AI/ML solutions
  • apply Generative AI algorithms to solve real world problems
  • architecting complex, scalable, and secure machine learning solutions
  • select and train and fine tune the right models
  • develop proof-of-concepts, and propose effective strategies for implementing AI and generative AI solutions at scale
  • design and run experiments, research new algorithms
  • Developing and deploying machine learning models and generative AI applications
  • Providing technical guidance on applying AI, machine learning, and generative AI responsibly and cost-efficiently
  • Sharing knowledge within the organization through mentoring, training, creating reusable AI/ML artifacts