ZipRecruiter

Log In

1

Ml Infrastructure Jobs in Oregon (NOW HIRING)

PointClickCare

(Canada) Principal ML System Engineer

OR · On-site +1

As the technical authority for the ML platform, the Principal Engineer will define the reference ... Define secure, cost-efficient integration and infrastructure patterns for connecting the platform ...

SentinelOne

Senior Backend Software Engineer, ObservoAI

OR · On-site +1

$122K - $161K/yr

Ideal candidates will have: * 5+ years of software engineering experience focused on distributed systems, data engineering, or ML infrastructure with expert-level proficiency in Go, Rust, or Java.

Vantor

Applied AI Scientist

OR · On-site

$128K - $215K/yr

Familiarity with Google Cloud Platform (GCP) , including large-scale AI/ML infrastructure. * Experience implementing model monitoring, evaluation pipelines, and automated retraining systems

Upstart

Senior Manager, Machine Learning

OR · On-site +1

Hands-on familiarity with end-to-end ML infrastructure, including experimentation pipelines, feature stores, and model monitoring. Ability to uplevel team's engineering practices and drive cross ...

Webflow

Senior Staff Software Engineer

OR · On-site +1

$122K - $161K/yr

Partner closely with data scientists, ML engineers, and product engineers to productionize statistical and AI/ML capabilities into reliable, real-time backend infrastructure. * Lead complex, multi ...

Chainguard

Security Engineer

OR · On-site +1

Support the hardening and monitoring of cloud infrastructure alongside senior cloud architects * Assist in securing AI/ML pipelines and agentic workflows as they scale across the company

CookUnity

Director, Data Science/ML

OR · On-site +1

Experience with cloud-based data infrastructure (AWS, GCP, Snowflake) and ML Ops tools (MLflow, Airflow, Kubeflow) Preferred requirements: * PhD or Master's degree in Computer Science, Statistics ...

Hitachi

Data Scientist I or II (MAD-BS-OR)

Hillsboro, OR · On-site +1

$121K - $167K/yr

Distributed systems and scalable ML infrastructure * MLOps practices (CI/CD, monitoring, model versioning) * Knowledge of: * Signal processing or physics-based modeling * Graph-based reasoning or ...

Chainguard

Senior Security Engineer (Cloud)

OR · On-site +1

$114K - $156K/yr

Experience securing or architecting AI/ML infrastructure or agentic workflows * Outstanding interpersonal and communication skills: you'll plan, coordinate, and build consensus with the Developer ...

next page

Showing results 1-20

All JobsMl Infrastructure JobsMl Infrastructure Jobs in Oregon

Ml Infrastructure information

What is ML infrastructure?

ML Infrastructure refers to the underlying systems, tools, and processes that enable the development, deployment, and scaling of machine learning models. This includes data storage and management, computing resources, model training and serving environments, monitoring, and automation tools. ML Infrastructure ensures that data scientists and engineers can efficiently build, test, and maintain machine learning applications in a reliable and reproducible manner. It is a crucial foundation for organizations looking to operationalize AI and machine learning solutions at scale.

What are some common challenges faced by professionals working in ML infrastructure roles?

Professionals in ML Infrastructure often encounter challenges related to scaling systems to handle large volumes of data, ensuring reliable deployment pipelines, and maintaining reproducibility across different environments. They must also collaborate closely with data scientists and engineers to streamline workflows and address issues like version control and model monitoring. Staying updated with rapidly evolving tools and best practices is essential, and balancing stability with innovation is a frequent aspect of the role.

What are the key skills and qualifications needed to thrive as an ML infrastructure engineer, and why are they important?

To thrive as an ML Infrastructure Engineer, you need a strong background in software engineering, cloud computing, and machine learning concepts, often supported by a degree in computer science or a related field. Proficiency with containerization tools (like Docker and Kubernetes), cloud platforms (such as AWS, GCP, or Azure), and CI/CD systems is critical. Excellent problem-solving, collaboration, and communication skills help you efficiently work with data scientists and DevOps teams. These skills and qualities are vital for building scalable, reliable ML systems that support rapid experimentation and deployment in production environments.

What is the difference between Ml Infrastructure vs Data Engineer?

AspectML InfrastructureData Engineer
Required CredentialsBachelor's in CS, Data Science, or related; knowledge of cloud platformsBachelor's in CS, Software Engineering, or related; experience with databases and ETL tools
Work EnvironmentFocus on deploying and maintaining ML systems, cloud environments, and infrastructure toolsDesigning, building, and managing data pipelines and storage solutions
Industry UsageUsed in AI/ML teams to support model deployment and scalabilityUsed across data-driven organizations for data management and analytics

ML Infrastructure specialists focus on deploying, scaling, and maintaining machine learning systems and infrastructure, while Data Engineers primarily build and manage data pipelines and storage solutions. Both roles require technical skills and often collaborate, but their core responsibilities differ in focus and tools used.

What are popular job titles related to Ml Infrastructure jobs in Oregon?

For Ml Infrastructure jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Ml Infrastructure jobs in Oregon look for?

The top searched job categories for Ml Infrastructure jobs in Oregon are:

What cities in Oregon are hiring for Ml Infrastructure jobs?

Cities in Oregon with the most Ml Infrastructure job openings:

Ml Infrastructure jobs near you
Infographic showing various Ml Infrastructure job openings in Oregon as of August 2026, with employment types broken down into 86% Full Time, 11% Part Time, and 3% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution.

Senior Software Engineer, AI/ML Platform

Salem, OR • On-site, Remote

Agility Robotics
Industrial Automation Equipment Manufacturing • 51 - 200 employees
Learn more about Agility Roboticsexternal

$197K - $307K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 9 days ago

Job description

Agility's commercially deployed humanoids operate alongside teams in warehouses, manufacturing facilities, and distribution centers—tackling physically demanding and repetitive tasks while enabling workers to focus on higher-value work. With industry-leading safety standards and years of proven deployment data, we're pioneering a new era of automation that enhances human potential.

About The Role

Join the team building the machine learning platform to power fleet-scale humanoid robotics. As a senior engineer on the ML Infrastructure and Platform group, you will help architect and build the foundational infrastructure for AI and machine learning operations at Agility. This includes the platform layer for data collection and processing, training, sim and real evaluation, and model management and observability.

Your work will empower our AI teams across perception, controls, skills, and innovation to build and deploy next-generation robot foundation models and end-to-end policies for humanoid robots by providing tools to develop and operationalize machine learning at scale. 

Key Responsibilities

Execution and Technical Ownership

    • Contribute to the design and implementation of the ML platform for orchestrating the end to end AI flywheel of data processing, training, evaluation, and deployment 
    • Develop reliable workflows across cloud compute, Kubernetes, and continuous automation
    • Build core infrastructure components such as the model registry, feature store and experiment tracking tooling.
    • Own developer-facing APIs and CLI tools that make ML workflows simple and reproducible. 
    • Implement the CI/CD lifecycle for ML that enable continuous retraining, automated testing, and seamless model delivery to production environments

Collaboration

    • Work closely with the Staff ML Infra Engineer and cross-functional stakeholders (AI researchers and robotics engineers) to understand requirements and translate them into scalable solutions/systems.
    • Partner with data platform engineers to integrate ML orchestration and metadata tracking tools with our existing data lake and pipelines.

Engineering Excellence, Growth and Impact: 

    • Apply MLOps best practices: reproducibility, lineage, rollback, monitoring and governance. 
    • Mentor junior engineers and influence the broader cloud platform organization's roadmap.
    • Contribute to internal discussions on platform architecture, reliability, and scalability alongside the broader ML and data platform team
What We're Aiming For (MLOps Level 2)
  • Version-controlled ML pipelines (data, code, and config)
  • Automated and reproducible model training and evaluation
  • Continuous integration and delivery for ML workflows
  • Centralized experiment tracking and performance visualization
  • Standardized model packaging and deployment to production
  • Monitoring of models post-deployment
Required Qualifications
  • 5+ years of software engineering experience, with at least 2+ years working on ML infrastructure, data platforms or MLOps systems in production environments.
  • Experience building and maintaining components of modern ML platforms—such as experiment tracking, model registries, training pipelines, or deployment systems
  • Familiarity with orchestration and tracking tools (MLflow, WandB, Airflow, Kubeflow, etc.)
  • Proficiency with cloud-native platforms (AWS, GCP, or Azure), containers, and IaC (e.g., CDK, Terraform)
  • Hands-on experience with processing or modeling multimodal data(sensor logs, camera streams, behaviour traces etc).
  • Comfortable collaborating cross-functionally with research scientists, data engineers, and robotics/autonomy teams to ship infrastructure used by others
Bonus Qualifications
  • Experience with robotics, autonomous vehicles, drones or embedded ML.
  • Contributions to open-source ML infrastructure or MLOps tooling a plus. 
Why This Role?
  • Build from the start Join at a pivotal moment - help shape the ML platform layer as its being defined, not inherited. 
  • High impact: Your work will directly enable faster, safer, and more intelligent robotic behaviors at scale
  • Technical Frontier: You will work directly on enabling the next frontier of AI in real production settings
  • Remote-friendly with a strong engineering culture and a fully distributed team.

The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future.

Anticipated Base Salary Range
$197,000—$307,000 USD

In addition to base pay, our competitive total rewards package consists of the following for full-time employees:

  • 401(k) Plan: Includes a 6% company match.
  • Equity: Company stock options.
  • Insurance Coverage: 100% company-paid medical, dental, vision, and short/long-term disability insurance for employees.
  • Benefit Start Date: Eligible for benefits on your first day of employment.
  • Well-Being Support: Employee Assistance Program (EAP).
  • Time Off:
    • Exempt Employees: Flexible, unlimited PTO and 12 company holidays, including a winter shutdown.
    • Non-Exempt Employees: 10 vacation days, paid sick leave, and 12 company holidays, including a winter shutdown, annually.
  • On-Site Perks: Catered lunches four times a week and a variety of healthy snacks and refreshments at our Salem and Pittsburgh locations.
  • Parental Leave: Generous paid parental leave programs.
  • Work Environment: A culture that supports flexible work arrangements.
  • Growth Opportunities: Professional development and tuition reimbursement programs.
  • Relocation Assistance: Provided for eligible roles.
  • Annual Discretionary Bonus: Provided for eligible roles.

All of our roles are U.S.-based. Applicants must have current authorization to work in the United States.

Agility Robotics is committed to a work environment in which all individuals are treated with respect and dignity. Each individual has the right to work in a professional atmosphere that promotes equal employment opportunities and prohibits unlawful discriminatory practices, including harassment. Therefore, it is the policy of Agility Robotics to ensure equal employment opportunity without discrimination or harassment on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, age, disability, marital status, citizenship, national origin, genetic information, or any other characteristic protected by law. Agility Robotics prohibits any such discrimination or harassment.

Agility Robotics does not accept unsolicited referrals from third-party recruiting agencies.  We prioritize direct applicants and encourage all qualified candidates to apply directly through our careers page.  If you are represented by a third party, your application may not be considered.  To ensure full consideration, please apply directly.

Apply