ML Infrastructure Engineer

We're looking for engineers who bring expertise across the AI space, including ML platform design, cloud hosted AI services, foundational AI models, LLMs, Edge AI, and cutting-edge AI research; our list of breakthrough products and technologies is growing at a rapid pace. Central AI is critical to ADI’s future and presents opportunities to select from a variety of project areas as you and our AI-driven business grow.

Finally, we need our team to be versatile, willing to take risks, able lead projects quickly, and be enthusiastic about new technologies and solutions.

Location:

San Jose, CA or Boston, MA

Responsibilities

• As a ML Infrastructure Engineer, you help build, deliver, and optimize software systems to enable AI/ML solutions.
• Design and implement machine learning systems and workflows to support real-time training, testing, and deployment of AI models.
• Design and implement distributed cloud GPU training approaches for deep learning model training and evaluation.
• Build end-to-end machine learning pipelines and integrate them into product and business system workflows.
• Architect and own the build-release continuous integration processes of our deep learning software components that are built, tested, and released on various DL frameworks (Tensorflow, PyTorch, JAX, etc.)
• Propose, implement, and deploy efficient and scalable Dev Ops solutions to allow our fast-growing team to release software more frequently while maintaining high-quality and top performance.
• Automate away recurring tasks (DL algorithm accuracy and performance regression detection, designing and developing new quality control measures, e.g., code analysis) while employing and advancing best practices.

Qualifications

• 3+ years of experience in software engineering, including experience with distributed systems real-time streaming.
• Degree in Computer Science or a related technical field.
• Strong system level programming skills (Python, shell scripting, etc.) and familiarity with Linux system administration.
• Hands-on experience with infrastructure engineering, modern Dev Ops processes, CI/CD, and Git Hub.
• Experience with ML frameworks (Pytorch, Tensorflow, etc.) and model distribution frameworks (Torch Serve, etc.).
• Experience with developing, implementing, and optimizing container orchestration systems, such as Kubernetes.
• Ability to work with and manage cloud data technologies, such as Kafka, Elastic Search, Terraform, Air Flow, or Dagster.
• Excellent debugging and optimization skills.
• Experience working on software teams and willingness to work in a fast-paced environment.

For positions requiring access to technical data, Analog Devices, Inc. may have to obtain export licensing approval from the U.S. Department of Commerce
- Bureau of Industry and Security and/or the U.S. Department of State
- Directorate of Defense Trade Controls. As such, applicants for this position – except US Citizens, US Permanent Residents, and protected individuals as defined by 8 U.S.C. 1324b(a)(3) – may have to go through an export licensing review process.