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Mlops Machine Learning Engineer Jobs in Oregon (NOW HIRING)

Senior/Staff Machine Learning Engineer - Ads

OR ยท On-site +1

$205K - $355K/yr

Finally, you will help build the foundational patterns that ML engineers will use for years to come as we ramp up our effort to introduce machine learning into our platform * Collect and gather ...

Machine Learning Engineer 5 - Globalization

OR ยท On-site +1

$466K - $750K/yr

We are looking for an experienced Machine Learning Engineer with deep expertise in training and inference efficiency for Large Language Models (LLMs), Multimodal LLMs, and other media ML models. In ...

Data Engineer

OR ยท On-site +1

$114K - $137K/yr

You'll partner closely with Machine Learning Engineers, Data Scientists, and Software Engineers to ... Collaborate with ML Engineers and cross-functional partners to support MLOps best practices ...

Staff AI Engineer, Perception

Salem, OR ยท On-site

$207K - $323K/yr

The Perception team is looking for a staff machine learning engineer to own the design and ... Experience with MLOps such as (but not limited to) data annotation services, data storage, model ...

Staff AI Engineer, Perception

Salem, OR ยท On-site +1

$207K - $323K/yr

The Perception team is looking for a staff machine learning engineer to own the design and ... Experience with MLOps such as (but not limited to) data annotation services, data storage, model ...

Staff AI Engineer, Perception

Salem, OR ยท On-site

$207K - $323K/yr

The Perception team is looking for a staff machine learning engineer to own the design and ... Experience with MLOps such as (but not limited to) data annotation services, data storage, model ...

Lead AI/ML Engineer

OR ยท On-site +1

$180K - $230K/yr

... machine learning engineers. * Experience with Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), or AI agents. * Experience deploying AI solutions using MLOps best ...

New

Oversee the establishment of best practices for MLOps, security, and performance monitoring to ... Deep expertise in building highly available, low-latency machine learning systems, including ...

Senior Data Engineer

OR ยท On-site +1

$105K - $143K/yr

As a Senior Data Engineer, you will be pivotal in optimizing and scaling our foundational Snowflake ... Operationalize Machine Learning: Design and maintain MLOps pipelines to support the seamless ...

Machine Learning Tutor

Portland, OR ยท Remote

$18 - $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 ...

Managing MLE-heavy engineering and research efforts to optimize our core unsecured personal loan ... Experience * 6+ years of experience developing and deploying machine learning models in production ...

Machine Learning Tutor

OR ยท Remote

$18 - $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 ...

Machine Learning Tutor

Eugene, OR ยท Remote

$18 - $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 ...

You will collaborate with scientists, pathologists, bioinformaticians, and software engineers to scale machine learning approaches that advance personalized oncology diagnostics and tumor-informed ...

Required Qualifications Experience * 10+ years of experience as a Machine Learning Engineer ... with MLOps tooling such as AWS SageMaker, Azure ML, and MLflow for enterprise-scale ML.

Showing results 41-60

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

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

Senior/Staff Machine Learning Engineer - Ads

Nextdoor

OR โ€ข On-site, Remote

$205K - $355K/yr

Full-time

Re-posted 15 days ago


Job description

#TeamNextdoor

Nextdoor (NYSE: NXDR) is the essential neighborhood network. Neighbors, public agencies, and businesses use Nextdoor to connect around local information that matters in more than 350,000 neighborhoods across 11 countries. Nextdoor builds innovative technology to foster local community, share important news, and create neighborhood connections at scale. Download the app and join the neighborhood at nextdoor.com.

Meet Your Future Neighbors

At Nextdoor, machine learning is one of the most important teams we are growing. Machine learning is starting to transform our product through personalization, driving major impact across different parts of our platform, including newsfeed, notifications, ad relevance, connections, search, and trust. Our machine learning team is lean but hungry to drive even more impact and make Nextdoor the neighborhood hub for local exchange. We believe that ML will be integral to making Nextdoor valuable to our members. We also believe that ML should be ethical and encourage healthy habits and interaction, not addictive behavior. We are looking for great engineers who believe in the power of the local community to empower our members to make their communities great places to live.ย 

At Nextdoor, we operate in an AI-first environment and expect every team member to actively use AI tools as part of their workflow. We aren't looking for prompt engineers; we're looking for people who use tools like Claude, Gemini, ChatGPT, and Glean to challenge their own thinking and take full ownership of AI-assisted outputs.

We also offer a warm and inclusive work environment that embraces a hybrid employment model, blending an in office presence and work from home experience for our valued employees. The hiring team will go over these expectations with you if you are being considered for a role near one of our offices in San Francisco, Los Angeles, Chicago, Dallas, New York, and London.

The Impact You'll Make
  • You will be part of a scrappy and impactful team building data-intensive products, working with data and features, building machine learning models, and sharing insights around data and experiments. You will work closely with the Product and Data Science teams on a daily basis. Finally, you will help build the foundational patterns that ML engineers will use for years to come as we ramp up our effort to introduce machine learning into our platform
  • Collect and gather datasets to build machine learning (ML) models that make real-time decisions for the Nextdoor platform
  • Analyze datasets and use important features to build low-latency models for decisions that need to be made quickly
  • Deploy ML models into production environments and integrate them into the product
  • Run and analyze live user-facing experiments to iterate on model quality by measuring impact on business metrics
  • Collaborate with other engineers and data scientists to create optimal experiences on the platform
  • Participate in in-person Nextdoor events such as trainings, off-sites, volunteer days, and team building exercises
  • Build in-person relationships with team members and contribute to Nextdoor's company culture
What You'll Bring To The Team
  • B.S. in Computer Science, Applied Math, Statistics, Computational Biology, or a related field
  • 5+ years of industry/academic experience in applying machine learning at scale
  • Experience in building ML models for advertising products
  • Proven engineering skills. Experience in writing and maintaining high-quality production code
  • Ability to work with and analyze large amounts of data
  • Ability to succeed in a dynamic startup environment
Rewards

Compensation, benefits, perks, and recognition programs at Nextdoor come together to create our total rewards package. Compensation will vary depending on your relevant skills, experience, and qualifications.

The starting salary for this role is expected to range from $205,000 to $355,000 on an annualized basis, or potentially greater in the event that your 'level' of proficiency exceeds the level expected for the role. The salary range will be determined by the candidate's geographic location.

We expect to award a meaningful equity grant for this role. With quarterly vesting, your first vest date will take place within 3 months of your start date.

When it comes to benefits, we have you covered! Nextdoor employees can choose between a variety of health plans, including a 100% covered employee only plan option, and we also provide a OneMedical membership for concierge care.

At Nextdoor, we empower our employees to build stronger local communities. To create a platform where all feel welcome, we want our workforce to reflect the diversity of the neighbors we serve. We encourage everyone interested in our mission to apply. We do not discriminate on the basis of race, gender, religion, sexual orientation, age, or any other trait that unfairly targets a group of people. In accordance with the San Francisco Fair Chance Ordinance, we always consider qualified applicants with arrest and conviction records.

For information about our collection and use of applicants' personal information, please see Nextdoor's Personnel Privacy Notice, found here.

#LI-Hybrid #LI-Remote