About Analog Devices Analog Devices, Inc. (NASDAQ: ) 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 PossibleTM.
Learn more at and on and.
Senior Software Engineer - AWS Cloud Architect + AI (MLOps) 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 PossibleTM.
Learn more at 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 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 Job Req Type: ExperiencedRequired Travel: Yes, 10% of the timeShift Type: 1st Shift/Days