ML Engineer

Role overview This machine learning engineering role combines production ML systems work with development of generative AI applications. You would build and operate cloud-based capabilities, from data preparation and model tuning to deployment, monitoring, and security, while working with client stakeholders to shape practical AI solutions.

Responsibilities - Build scalable infrastructure and CI/CD workflows for training and deploying machine learning models. - Monitor models in production and improve their performance, hosting, and inference efficiency. - Develop generative AI applications, including large language model solutions, retrieval-augmented generation infrastructure, and search capabilities. - Prepare and analyze datasets, then develop or fine-tune models for the intended use case. - Apply security and compliance considerations throughout AI solution design and delivery. - Work with client stakeholders to define requirements and deliver robust solutions.

Requirements - Strong software engineering skills and experience in machine learning engineering, including model hosting, inference optimization, and model registry management. - Programming experience with Python and R, and familiarity with machine learning methods and data preparation. - Experience building cloud-native AI solutions on a major cloud platform such as AWS, Azure, or GCP. - Knowledge of CI/CD, DevOps, infrastructure as code, and cloud infrastructure such as networking, identity and access management, compute, and databases. - Familiarity with model evaluation and frameworks such as TensorFlow or PyTorch. - Experience with containers and orchestration tools such as Docker and Kubernetes; understanding of Agile methods.

Nice to have The source does not identify additional preferred qualifications beyond the listed tools and experience.

Benefits and work setup The role may require working onsite at an office or client location depending on project needs. U.S. work authorization is required; visa sponsorship is unavailable. Full-time benefits listed in the source include medical, dental, and vision plans, disability and life insurance, a 401(k) plan, an employee assistance program, and a connectivity stipend. Some professional development reimbursement and charitable giving match programs may be available subject to eligibility and approval.