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, AI, and software technologies into solutions that combat climate change, reliably connect humans and the world, and help drive advancements in automation and robotics, mobility, healthcare, energy and data centers. With revenue of more than $11 billion in FY25, ADI ensures today's innovators stay Ahead of What's Possible. Learn more at www.analog.com and on LinkedIn and X.
Duties
Design, develop and maintain scalable and efficient Artificial Intelligence/Machine Learning ("AI/ML") systems that solve complex problems. Collaborate with cross-functional teams, including product managers, UX designers, and software engineers to gather requirements and design appropriate solutions. Lead the development of end-to-end AI/ML pipelines, including data preprocessing, model training, prompt engineering, and performance evaluation. Participate in code reviews, architecture discussions, and technical planning. Optimize AI/ML model performance and ensure robustness, fairness, and explainability. Monitor AI/ML system performance, troubleshoot issues, and provide timely resolutions. Implement data security and privacy measures to protect sensitive information. Continuously evaluate and recommend improvements to our data infrastructure, tools, and processes. Stay up to date with emerging trends and technologies in the fields of AI and ML. Mentor junior engineers and contribute to best practices in AI/ML development.
In this role, these duties are performed in support of the team's AI/ML systems for tactile sensing and robot learning: developing end-to-end AI/ML pipelines over large multimodal datasets, including video, tactile, and time-series sensor data; training, evaluating, and optimizing models, including distributed multi-node training with checkpointing and fault recovery; optimizing and deploying trained models to their target compute environments, including GPU-accelerated and embedded runtimes; monitoring deployed model and system performance and resolving issues; and mentoring engineers on AI/ML development practices.
Engineering foundations
- 5+ years production infrastructure; strong Python plus one systems language (Go/Rust/C++)
- Expert Linux, networking, and debugging across the full stack
- Infrastructure-as-code (Terraform/Bicep) and containers, including GPU-enabled runtimes
Cloud & orchestration
- Production cloud experience (Azure preferred): IAM, storage, managed compute, cost control
- Kubernetes with GPU workloads: scheduling, autoscaling, quotas
MLOps
- Distributed training infrastructure: multi-node GPU, checkpointing, fault recovery
- Experiment tracking, model registry, dataset/artifact versioning
- ML CI/CD with automated evaluation gates and rollback
- Data pipelines for large multimodal datasets (video, tactile, time series)
- Observability: GPU utilization, drift, data quality
Edge deployment
- Model optimization for constrained targets: quantization, ONNX, TensorRT
- Deployment to embedded hardware (Jetson or similar) with OTA updates and rollback
- Awareness of latency constraints in closed-loop control
Collaboration
- Proven record turning research prototypes into supported production systems
- Mentoring engineers and driving practice adoption across a team
- Clear design docs and runbooks
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.
EEO is the Law: Notice of Applicant Rights Under the Law.
Job Req Type: ExperiencedRequired Travel: Yes, 10% of the time
Shift Type: 1st Shift/DaysThe expected wage range for a new hire into this position is $144,000 to $198,000.
Actual wage offered may vary depending on work location, experience, education, training, external market data, internal pay equity, or other bona fide factors.
This position qualifies for a discretionary performance-based bonus which is based on personal and company factors.
This position includes medical, vision and dental coverage, 401k, paid vacation, holidays, and sick time, and other benefits.
Skills Required
- 5+ years of production infrastructure experience
- Strong Python and proficiency in at least one systems language: Go, Rust, or C++
- Expertise in Linux, networking, and full-stack debugging
- Experience with infrastructure as code using Terraform or Bicep
- Experience with containers and GPU-enabled runtimes
- Production cloud experience, preferably Azure, including IAM, storage, managed compute, and cost control
- Kubernetes experience with GPU workloads, including scheduling, autoscaling, and quotas
- Experience building distributed training infrastructure with multi-node GPUs, checkpointing, and fault recovery
- Experience with experiment tracking, model registries, and dataset or artifact versioning
- Experience implementing ML CI/CD with automated evaluation gates and rollback
- Experience building data pipelines for large multimodal datasets
- Experience with observability for GPU utilization, model drift, and data quality
- Experience optimizing models for constrained targets using quantization, ONNX, or TensorRT
- Experience deploying models to embedded hardware such as Jetson, including OTA updates and rollback
- Awareness of latency constraints in closed-loop control
- Proven ability to turn research prototypes into supported production systems
- Experience mentoring engineers and driving practice adoption across a team
- Ability to create clear design documents and runbooks
Analog Devices Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Analog Devices and has not been reviewed or approved by Analog Devices.
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Retirement Support — The 401(k) program is described as a standout feature, with company contribution up to 8% of base salary and immediate vesting. This structure strengthens long-term value even when cash compensation perceptions vary.
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Healthcare Strength — Health coverage is positioned as comprehensive, including medical, dental, and vision options along with disability and life insurance. Day-one eligibility and multiple plan choices add to perceived robustness.
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Leave & Time Off Breadth — Paid time off appears broad, with vacation ranging from roughly 17–25 days and increasing up to five weeks with tenure, alongside sick time and paid holidays. Parental leave and related time-off provisions further expand coverage.
Analog Devices Insights
What We Do
Analog Devices, Inc. (NASDAQ: ADI) operates at the center of the modern digital economy, converting real-world phenomena into actionable insight with its comprehensive suite of analog and mixed signal, power management, radio frequency (RF), and digital and sensor technologies. ADI serves 125,000 customers worldwide with more than 75,000 products in the industrial, communications, automotive, and consumer markets. ADI is headquartered in Wilmington, MA.
