About Analog Devices

Analog Devices, Inc. (NASDAQ: ADI ) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, and software technologies into solutions that help drive advancements in digitized factories, mobility, and digital healthcare, combat climate change, and reliably connect humans and the world. With revenue of more than $9 billion in FY24 and approximately 24,000 people globally, ADI ensures today's innovators stay Ahead of What's Possible™. Learn more at www.analog.com and on LinkedIn and Twitter (X).

          

Senior Machine Learning Operations (MLOps) Engineer

Analog Devices, Inc. (NASDAQ: ADI ) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, and software technologies into solutions that help drive advancements in digitized factories, mobility, and digital healthcare, combat climate change, and reliably connect humans and the world. With revenue of more than $9 billion in FY24 and approximately 24,000 people globally, ADI ensures today's innovators stay Ahead of What's Possible™. Learn more at www.analog.com and on LinkedIn and Twitter (X).

This role is within the global XOps team -- which includes MLOps, LLMOps, AgentOps and DevOps – whose mission is to deliver a world-class AI/ML developer experience for our software engineers and data scientists. You will join a high-performance, mission-driven interdisciplinary team that spans data science, software engineering, product management, cloud architecture, and security expertise. We believe in a culture founded on trust, mutual respect, growth mindsets, and an obsession for building extraordinary products with extraordinary people.

Role Summary

As a Senior MLOps Engineer (individual contributor), you will bring deep technical expertise, the ability to handle complex assignments end-to-end, and make decisions with broad impact beyond individual tasks. You will independently design and optimize complete systems, resolve technical issues via systematic analysis, and apply industry best practices and advanced methodologies for continuous improvement. You’ll lead the development of major ML/AI operational features that span multiple aspects of the ML/AI developer experience— from infrastructure to pipelines, deployment, monitoring, governance, and cost/risk optimization.

Key Responsibilities

Operational Excellence

• Foster and contribute to a culture of operational excellence grounded in high performance, mission focus, trust, and interdisciplinary collaboration.
• Drive proactive capability and process enhancements that strengthen the ML/AI platform’s long‑term reliability, developer experience, and operational maturity.
• Design and implement resilient cloud-based ML/AI infrastructure that improves learnability, flexibility, extensibility, interoperability, and scalability.
• Lead efforts to optimize cost efficiency, system performance, and operational risk mitigation through data-driven strategies and analytics across ML/AI workloads.

ML/AI Cloud Operations & Engineering

• Architect and implement scalable AWS ML/AI infrastructure supporting the end-to-end lifecycle of models, agents, and services.
• Establish governance frameworks for provisioning, monitoring, drift detection, and lifecycle management in line with industry best practices.
• Define principled evaluation pathways for GenAI/LLM/Agent POCs across the organization.
• Lead Kubernetes cluster management for ML workflows and guide the selection/implementation of workflow orchestration systems (Argo, Kubeflow).
• Develop IaC (AWS CDK, Terraform) and GitOps automations to streamline deployment and management.
• Monitor and optimize cloud infrastructure, ML pipelines, and model workloads for cost, reliability, and performance.
• Collaborate cross-functionally with engineering, science, product, design, and security teams to translate requirements into scalable ML/AI solutions.

Required Skills & Experience

• Deep understanding of the Data Science Life Cycle (DSLC) and demonstrated ability to scale ML/AI solutions from prototype to production.
• Expertise in feature stores, model registries, and model governance frameworks (e.g., auditability, explainability).
• Experience with ML observability tools (drift detection, performance dashboards, SLA/SLO monitoring).
• Experience with Ray for scalable training, tuning, and serving pipelines; RL experience a plus.
• Advanced proficiency in IaC/GitOps (Terraform, AWS CDK, ArgoCD).
• Hands-on experience managing Kubernetes clusters and orchestrating ML workflows (Argo, Kubeflow, Airflow).
• Solid understanding of foundation models (LLMs) and enterprise ML/AI applications.
• Strong AWS DevOps experience across relevant services.
• Proven ability to optimize cloud/ML infrastructure for scalability and cost.
• Excellent communication and cross-functional influence skills.
• Experience leading large-scale, complex features with wide impact.
• Customer-centric mindset and strong organizational skills.
• Collaborative, supportive team contributor.

Preferred Skills – Robotics, ROS, and Industrial ML

• Experience building or deploying ML systems in robotics environments, especially where adaptability across tasks is required.
• Hands-on expertise with ROS (Robot Operating System), including creating, managing, and integrating ROS nodes, packages, and hardware interfaces.
• Experience developing ML/AI solutions for industrial automation, manufacturing robotics, or multi-skilled robot platforms.
• Familiarity with challenges in low-volume, high-variant (“batch of one”) manufacturing and designing ML systems that generalize across diverse tasks.
• Experience integrating ML pipelines with robot perception, control, or planning systems.
• Practical experience applying Vision-Language Models (VLMs) to robotics perception tasks, contextualization, or low-data classification.
• Understanding of robotic simulation tools (Gazebo, Isaac Sim, Webots) and how they integrate with ML workflows.
• Comfort working cross-functionally with robotics engineers to bridge manufacturing domain knowledge with ML operations.

#LI-BF1

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.

Analog Devices is an equal opportunity employer. We foster a culture where everyone has an opportunity to succeed regardless of their race, color, religion, age, ancestry, national origin, social or ethnic origin, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, parental status, disability, medical condition, genetic information, military or veteran status, union membership, and political affiliation, or any other legally protected group.

Job Req Type: Experienced

          

Required Travel: Yes, 10% of the time

          

Shift Type: 1st Shift/Days