Principal Engineer, AI/ML Software

Analog Devices; Boston (MA); On-site; USD 230,000 - 300,000; Full time

Benefits offered by this job

Partial telecommute (3 days/week)

Medical, Vision & Dental Coverage

401k & Paid Time Off

Job summary

Analog Devices, Inc. is seeking a Principal Engineer, AI/ML Software in Boston to design, build, and maintain robust MLOps systems and deploy AI/ML models on cloud-native platforms.

You will collaborate with data scientists and engineers to operationalize AI/ML solutions and ensure production readiness. The role involves ETL pipelines, scalable data stores, and implementing CI/CD with Terraform, Docker, and Kubernetes across AWS, GCP, and Azure.

Qualifications

• Bachelor’s degree in Computer Science, Information Technology, or a related field and five (5) years of experience as a software engineer building and maintaining machine learning software workflows.

Responsibilities

• Design, build, and maintain robust MLOps software systems.
• Support the development, deployment, testing, and monitoring of AI/ML models on cloud-native platforms.
• Collaborate with data scientists, software engineers, and stakeholders to operationalize AI/ML solutions and ensure production readiness.
• Implement and maintain ETL pipelines, automated workflows, and scalable data stores.
• Ensure high standards of model performance, security, and scalability through continuous monitoring of infrastructure.
• Guide the MLOps technology roadmap and evaluate emerging tools to enhance platform capabilities.
• Utilize Kubeflow and MLflow; work with Docker and Kubernetes for deployment.
• Deploy infrastructure using Terraform and manage resources on AWS, GCP, and Azure.
• Contribute to Agile processes and cross-functional team collaboration.

Skills

MLOps experience

Python

Distributed systems

RESTful APIs

Education

Bachelor's degree in Computer Science or related field

Master's degree in Computer Science or related field

Tools

Docker

Kubernetes

Terraform

MLflow

PyTorch

TensorFlow

Airflow

Apache Kafka

AWS

GCP

Azure

Job description

Job Details

Job Title: Principal Engineer, AI/ML Software. Job Requisition: 1010.557 / R264071. Job Location: Boston, Massachusetts. Job Type: Full Time. Rate of Pay: $230,475 - $300,000 per year.

Responsibilities

• Design, build, and maintain robust MLOps (Machine-Learning Operations) software systems.
• Support the development, deployment, testing, and monitoring of AI/ML models on modern cloud-native platforms.
• Collaborate with data scientists, software engineers, and stakeholders to operationalize AI/ML solutions and ensure their production readiness.
• Implement and maintain ETL pipelines, automated workflows, and scalable data stores.
• Ensure high standards of model performance, security, and scalability through continuous monitoring and enhancement of software infrastructure.
• Guide the MLOps technology roadmap and evaluate emerging tools and technologies to enhance platform capabilities.
• Utilize MLOps frameworks such as Kubeflow and MLflow, and work with containerization and orchestration tools including Docker and Kubernetes.
• Deploy infrastructure using Terraform and manage cloud-based resources on platforms such as GCP, AWS, and Azure.
• Contribute to Agile development processes and cross-functional team collaboration.

Requirements

• Must have a Bachelor’s degree in Computer Science, Information Technology, or a related field (or foreign education equivalent) and five (5) years of experience as a software engineer building and maintaining machine learning software workflows.
• In the alternative, Master’s degree in Computer Science, Information Technology, or a related field (or foreign education equivalent) and three (3) years of experience as a software engineer building and maintaining machine learning software workflows.
• Must also possess the following (quantitative experience requirements not applicable to this section):
  • Demonstrated Expertise (“DE”) designing, developing, and maintaining end-to-end machine learning (ML) pipelines, including data ingestion, preprocessing, model training, validation, and deployment (using PyTorch or TensorFlow);
  • Managing experiment tracking and model lifecycle with MLflow or CometML;
  • DE in technical leadership of production ML platforms and pipelines—leading a small, cross-functional team; setting standards, running design/code reviews, and mentoring junior engineers;
  • DE building scalable systems on cloud platforms, with hands-on experience designing fault-tolerant architectures, distributed training setups, multi-cloud strategies (using AWS, GCP, or Azure), and automating infrastructure tasks with Linux and shell scripting;
  • DE in containerization, orchestration, and MLOps/DevOps practices, including deploying ML models and pipelines with Docker and Kubernetes; implementing CI/CD and infrastructure-as-code (Terraform or AWS CloudFormation); and setting up monitoring and observability (Prometheus and Grafana);
  • DE developing distributed data processing pipelines for real-time or batch ML workflows (using Apache Airflow and Apache Kafka);
  • DE leading the design, building, and maintenance of scalable, robust, and secure RESTful APIs and microservices architectures using Python, with knowledge of computer networks and protocols.

Eligibility and Compliance

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.

Equal Opportunity Statement

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.

Benefits

• Partial telecommute benefit (3 days/week WFH).
• This position includes medical, vision and dental coverage, 401k, paid vacation, holidays, and sick time, and other benefits.

Job Type Information

Job Req Type: Experienced. Required Travel: No. Shift Type: 1st Shift/Days. 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.

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. Come join ADI – a place where Innovation meets Impact. For more than 55 years, Analog Devices has been inventing new breakthrough technologies that transform lives. At ADI you will work alongside the brightest minds to collaborate on solving complex problems that matter from autonomous vehicles, drones and factories to augmented reality and remote healthcare. ADI fosters a culture that focuses on employees through beneficial programs, aligned goals, continuous learning opportunities, and practices that create a more sustainable future.