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Mlops Machine Learning Engineer Jobs in Oregon (NOW HIRING)

May Mobility

Lead Machine Learning Engineer

OR · On-site +1

$102K - $134K/yr

Practical experience handling the "Long Tail" problem in Machine Learning. * Strong programming skills in Python/PyTorch in a Linux environment. * Functional understanding of LiDAR, Camera and Radar ...

Cresta

Staff Machine Learning Engineer

OR · On-site +1

Machine Learning Engineers at Cresta work across several high-impact AI initiatives. Final team placement is determined based on experience, strengths, and business needs. Current focus areas include:

Cresta

Senior Machine Learning Engineer

OR · On-site +1

$205K - $270K/yr

Machine Learning Engineers at Cresta work across several high-impact AI initiatives. Final team placement is determined based on experience, strengths, and business needs. Current focus areas include:

Quora

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning systems, building performant and reliable LLM applications and collaborating with our product team to ...

Quora

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning systems, building performant and reliable LLM applications and collaborating with our product team to ...

Quora

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning systems, building performant and reliable LLM applications and collaborating with our product team to ...

Quora

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning systems, building performant and reliable LLM applications and collaborating with our product team to ...

LMI

Bachelor's degree in Computer Science, Data Science, Software Engineering, or a related field. * 3+ years of experience in machine learning engineering, with particular emphasis on MLOps, model ...

May Mobility

Lead Machine Learning Engineer - Localization

OR · On-site +1

$102K - $134K/yr

As the Lead ML Engineer for Localization, you will build the production-grade feature extraction ... Architect and drive the technical roadmap for a production-grade localization machine learning ...

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All JobsMlops Machine Learning Engineer JobsMlops Machine Learning Engineer Jobs in Oregon

Mlops Machine Learning Engineer information

What does an MLOps machine learning engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

What are the key skills and qualifications needed to thrive as an MLOps machine learning engineer?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

How does an MLOps machine learning engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

What is the difference between Mlops Machine Learning Engineer vs Data Scientist?

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

Are MLOps machine learning engineers in demand?

MLOps machine learning engineers are in high demand due to the increasing adoption of AI and machine learning across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

Do MLOps Machine Learning Engineers need a degree?

MLOps Machine Learning Engineers typically do not require a formal degree but often have a background in computer science, data science, or related fields. Practical skills in machine learning, cloud platforms, and tools like Docker, Kubernetes, and CI/CD pipelines are highly valued. Certifications and hands-on experience can also enhance job prospects.

What are popular job titles related to Mlops Machine Learning Engineer jobs in Oregon?

For Mlops Machine Learning Engineer jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Mlops Machine Learning Engineer jobs in Oregon look for?

The top searched job categories for Mlops Machine Learning Engineer jobs in Oregon are:

What cities in Oregon are hiring for Mlops Machine Learning Engineer jobs?

Cities in Oregon with the most Mlops Machine Learning Engineer job openings:

Mlops Machine Learning Engineer jobs near you

Lead Machine Learning Engineer

May Mobility

OR • On-site, Remote

$102K - $134K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 23 days ago

Job description

We are seeking Machine Learning Leaders in the Autonomous Vehicle domain. As part of our team, you will play a critical role in enhancing May's Machine Learning capabilities both on and off the vehicle, in a commercial large-scale environment with high standards of quality.

Essential Responsibilities
  • Design, train and evaluate state of the art models for May's autonomous driving, simulation and ML Platform stack.
  • Leverage emerging techniques in the End-to-End driving, Vision Language Action (VLA), World or Foundation model domains to solve commercial-scale problems.  
  • Lead small teams of cross functional Engineers beyond the state of the art.
  • Define data balance, training experiment and evaluation practices to train efficiently at petabyte scale.
Skills and Abilities

Success in this role typically requires the following competencies:

  • Direct experience architecting & training VLA, MMLM, or Generative World Models for commercial-scale applications
  • Experience composing, processing and characterizing large (>100TB) multi-modal datasets
  • Experience analyzing and addressing long-tail failure cases in large models
  • Experience leading teams of 2-3 Engineers and communicating technical details to interdisciplinary leadership.
Qualifications and Experience

Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience:

Required
  • Extensive practical experience in one of the following domains:
    • Vision Language Action Models
    • Generative World Models
    • Foundation Models in Robotics
    • Data Centric AI
  • A minimum of 4 years of industry experience working on commercial robotics systems.
  • A minimum of 1 year mentoring ML Engineers in a commercial or lab environment.
  • Master's degree in Robotics, Computer Science, or Computer Engineering, or a field that requires a strong mathematical and/or engineering foundation.
  • Practical experience handling the "Long Tail" problem in Machine Learning.
  • Strong programming skills in Python/PyTorch in a Linux environment.
  • Functional understanding of LiDAR, Camera and Radar processing techniques.
Desirable
  • PhD and/or published research in the described specialty domains.
  • Familiar with common post-training techniques.
  • Experience deploying models to resource constrained and edge hardware
  • Functional understanding of C/C++/CUDA memory and threading models.
Physical Requirements
  • Standard office working conditions which includes but is not limited to:
    • Prolonged sitting
    • Prolonged standing
    • Prolonged computer use
  • Travel required? -  Low: 5%-10%

Benefits and Perks

  • Comprehensive healthcare suite including medical, dental, vision, life, and disability plans. Domestic partners who have been residing together at least one year are also eligible to participate. 
  • Health Savings and Flexible Spending Healthcare and Dependent Care Accounts available.
  • Rich retirement benefits, including an immediately vested employer safe harbor match.
  • Generous paid parental leave as well as a phased return to work. 
  • Flexible vacation policy in addition to paid company holidays.
  • Total Wellness Program providing numerous resources for overall wellbeing   
Don't meet every single requirement? Studies have shown that women and/or people of color are less likely to apply to a job unless they meet every qualification. At May Mobility, we're committed to building a diverse, inclusive, and authentic workforce, so if you're excited about this role but your previous experience doesn't align perfectly with every qualification, we encourage you to apply anyway! You may be the perfect candidate for this or another role at May.

Want to learn more about our culture & benefits? Check out our website!

May Mobility is an equal opportunity employer.  All applicants for employment will be considered without regard to race, color, religion, sex, national origin, age, disability, sexual orientation, gender identity or expression, veteran status, genetics or any other legally protected basis.   Below, you have the opportunity to share your preferred gender pronouns, gender, ethnicity, and veteran status with May Mobility to help us identify areas of improvement in our hiring and recruitment processes. Completion of these questions is entirely voluntary.  Any information you choose to provide will be kept confidential, and will not impact the hiring decision in any way. If you believe that you will need any type of accommodation, please let us know.

Note to Recruitment Agencies: May Mobility does not accept unsolicited agency resumes. Furthermore, May Mobility does not pay placement fees for candidates submitted by any agency other than its approved partners.

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