ZipRecruiter

Log In

1

Mlops Machine Learning Engineer Jobs in Portland, OR

Varsity Tutors

Machine Learning Tutor

Portland, OR · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Trimble

Machine Learning Data Scientist

Lake Oswego, OR · On-site

$122K - $165K/yr

Drive Innovation as our Next Data Engineer / Scientist (Predictive Analytics)! Ready to make a ... In this role, you will be at the forefront of developing predictive machine learning models ...

Deloitte

AI Data Engineer - Manager

Portland, OR

$121K - $145K/yr

Lead the development of AI models (e.g., machine learning, natural language processing, computer ... Understand and contribute to MLOps and LLMOps, focusing on operational capabilities and ...

Deloitte

AI Solutions Architect

Portland, OR

$66.75 - $88/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

Deloitte

Senior AI Engineer - SFL Scientific

Portland, OR

$110K - $152K/yr

Our engineering team leverages emerging technologies and best practices across data security ... MLOps specializing in AI and Machine Learning deployment * 4+ years of experience in designing ...

next page

Showing results 1-20

All JobsMlops Machine Learning Engineer JobsMlops Machine Learning Engineer Jobs in Portland, OR

Mlops Machine Learning Engineer information

See Portland, OR salary details

$33.4K

$136.6K

$205.2K

How much do mlops machine learning engineer jobs pay per year?

As of Jun 13, 2026, the average yearly pay for mlops machine learning engineer in Portland, OR is $136,560.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,600.00 and $164,400.00 per year, depending on experience, location, and employer.

Is MLOps harder than DevOps?

MLOps, as a specialized subset of DevOps focused on deploying and maintaining machine learning models, often involves additional challenges such as data management, model versioning, and monitoring. While both require skills in automation, scripting, and cloud environments, MLOps typically demands expertise in machine learning workflows and tools like TensorFlow or PyTorch, making it more complex in certain aspects compared to traditional DevOps.

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.

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 engineers in demand?

MLOps engineers are in high demand due to the increasing adoption of machine learning models in various industries. Their skills in deploying, managing, and scaling machine learning systems, along with knowledge of tools like Docker, Kubernetes, and cloud platforms, make them valuable in the job market.

What engineers make $500,000?

Senior machine learning engineers, including those specializing in MLOps, often reach or exceed $500,000 annually with experience, advanced skills, and in high-demand industries like tech or finance. Compensation can include base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

How much do MLOps engineers make?

MLOps engineers typically earn between $100,000 and $150,000 annually, with salaries increasing based on experience, location, and expertise in tools like Kubernetes, Docker, and cloud platforms. Senior roles or those with specialized skills can exceed $180,000 per year.

What are the key skills and qualifications needed to thrive as an MLOps Machine Learning Engineer, and why are they important?

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.
What are popular job titles related to Mlops Machine Learning Engineer jobs in Portland, OR? For Mlops Machine Learning Engineer jobs in Portland, OR, the most frequently searched job titles are:
What job categories do people searching Mlops Machine Learning Engineer jobs in Portland, OR look for? The top searched job categories for Mlops Machine Learning Engineer jobs in Portland, OR are:
Mlops Machine Learning Engineer jobs near you
Machine Learning Engineering Manager

Machine Learning Engineering Manager

Indeed

Portland, OR

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 5 days ago

Indeed rating

9.5

Company rating: 9.5 out of 10

Based on 6 frontline employees who took The Breakroom Quiz

7th of 189 rated software companies

Job description

Our Mission

As the world’s number 1 job site*, our mission is to help people get jobs. We strive to cultivate an inclusive and accessible workplace where all people feel comfortable being themselves. We're looking to grow our teams with more people who share our enthusiasm for innovation and creating the best experience for job seekers.

(*Comscore, Total Visits, March 2025)

Day to Day

At Indeed, we are committed to delivering exceptional experiences that connect job seekers with opportunities through innovative technology. We integrate machine learning at every step to create consistent, engaging, and secure experiences that meet the needs of our users. Our teams consist of Software Engineers, UX Designers, Product Managers, and Machine Learning professionals collaborating across regions to drive impactful business outcomes.

As a Machine Learning Engineering Manager, you will onboard and oversee junior scientists and technical leads, partnering closely with Product, Software Engineering, and UX teams. Your focus will include developing and innovating machine learning ecosystems that upgrade job seeker journey experience end to end

Responsibilities

  • Coach Machine Learning Engineers and Data Scientists on the Journey team to improve their performance, advise them on their career direction, and develop their qualifications.

  • Work to understand, prioritize, and plan the team’s work items without external guidance.

  • Ensure delivery of machine learning solutions, set expectations for what can be done and by when, and prioritize incoming projects.

  • Improve existing Agile, ML, and A/B testing processes and develop new ones.

  • Scope projects, gather and improve on requirements, and delegate work effectively.

  • Partner with and provide project direction and feedback to cross-functional peers, including Product Managers, Software Engineers.

  • Remove roadblocks and give individual contributors autonomy and ownership.

  • Brainstorm with teammates about practical experimental design, navigating production codebases, and model development.

  • Be prepared to closely engage and contribute directly to implementation when necessary.

Skills/Competencies

  • Requires a Bachelor’s degree in Computer Science, Mathematics, Statistics, or related field and a minimum of 8 years of related experience; or a Master’s degree with a minimum of 6 years of experience; or a PhD with a minimum of 3 years experience

  • Demonstrated achievement as a Manager in Machine Learning Engineering, overseeing teams of 3 or more, and addressing intricate, large-scale problems

  • Well-versed in coding (Python, Java, Go, or C++) and experience with SQL Databases like Presto, and data processing frameworks like Spark

  • Have full-stack experience in data collection, aggregation, analysis, visualization, productionisation, and monitoring

  • Highly effective in coaching Machine Learning Engineers, facilitating qualification enhancement, and fostering career development

Salary Range Transparency

Tier 1 - United States of America 163,000 - 245,000 USD per year

Tier 2 - United States of America 182,000 - 272,000 USD per year

Tier 3 - United States of America 199,000 - 299,000 USD per year

Tier 4 N/A

Tier 5 - United States of America 227,000 - 341,000 USD per year

Salary Range Disclaimer

The salary range for this role reflects the minimum and maximum compensation for the role. Offers are typically made between the range minimum and the range midpoint. Actual compensation will be determined based on job-related skills, experience, and expertise, as evaluated during the interview process. The range(s) listed is just one component of Indeed's total compensation package for employees. Other rewards may include quarterly bonuses, Restricted Stock Units (RSUs), a Paid Time Off policy, and many region-specific benefits. Compensation may also vary based on where a role is performed, as work locations are grouped into geographic pay tiers to reflect cost of labor differences in different geographic markets. Candidates can view geographic pay tiers by location on our career site (https://www.indeed.com/careers/paytiers), and recruiters can confirm how location is considered for a specific role.

Benefits - Health, Work/Life Harmony, & Wellbeing

We care about what you care about. We have a multitude of benefits to support Indeedians, as well as their pets, kids, and partners including medical, dental, vision, disability and life insurance. Indeedians are able to enroll in our company’s 401k plan, as well as an equity-based incentive program. Indeedians will also receive open paid time off, 11 paid holidays a year and up to 26 weeks of paid parental leave. For more information, select your country and learn more about our employee benefits, program, & perks at https://www.indeed.com/careers/benefits !

Equal Opportunities and Accommodations Statement

Indeed is deeply committed to building a workplace and global community where inclusion is not only valued, but prioritized. We’re proud to be an equal opportunity employer, seeking to create a welcoming and diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, family status, marital status, sexual orientation, national origin, genetics, neuro-diversity, disability, age, or veteran status, or any other non-merit based or legally protected grounds.

Indeed provides reasonable accommodations to qualified individuals with disabilities in the employment application process. To request an accommodation, please visit https://www.indeed.com/careers/accommodations. If you are requesting accommodation for an interview, please reach out at least one week in advance of your interview.

For more information about our commitment to equal opportunity/affirmative action, please visit our Careers page (https://www.indeed.com/careers).

Inclusion & Belonging

Inclusion and belonging are fundamental to our hiring practices and company culture, forming an integral part of our vision for a better world of work. At Indeed, we’re committed to the wellbeing of our employees and on a mission to make this the best place to work and thrive. We believe that fostering an inclusive environment where every employee feels respected and accepted benefits everyone, fueling innovation and creativity.

We value diverse experiences, including those who have had prior contact with the criminal legal system. We are committed to providing individuals with criminal records, including formerly incarcerated individuals, a fair chance at employment.

Those with military experience are encouraged to apply. Equivalent expertise demonstrated through a combination of work experience, training, military experience, or education is welcome.

Indeed’s Employee Recruiting Privacy Policy

Like other employers Indeed uses our own technologies to help us find and attract top talent from around the world. In addition to our site’s user and privacy policy found at https://www.indeed.com/legal , we also want to make you aware of our recruitment specific privacy policy found at https://www.indeed.com/legal/indeed-jobs .

Agency Disclaimer

Indeed does not pay placement fees for unsolicited resumes or referrals from non-candidates, including search firms, staffing agencies, professional recruiters, fee-based referral services, and recruiting agencies (each individually, an "Agency"), subject to local laws. An Agency seeking a placement fee must obtain advance written approval from Indeed's internal Talent Acquisition team and execute a fee agreement with Indeed for each job opening before making a referral or submitting a resume for that opening.

AI Notice

Indeed is committed to ensuring fairness and transparency throughout our hiring process. We use artificial intelligence (AI) tools to assist in the screening, assessment, and selection of applicants for this position by analyzing information provided in resumes and applications. Our use of AI does not replace human decision-making.

Unless otherwise notified, Indeed does not use AI constituting an AEDT or an ADMT as those tools are defined in applicable laws.

Reference ID: 47119

The deadline to apply to this position is 6/9. Job postings may be extended at the hiring team’s discretion based on applicant volume.

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

#INDDATA

Reference ID: 47119

Apply