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Mlops Machine Learning Engineer Jobs in Oregon (NOW HIRING)

Cresta

OR · On-site

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:

Vectara

OR · On-site

$122K - $161K/yr

... Engineering, Mathematics, or a related field. * 8+/7+ years of professional work experience after BS/MS applying machine learning to real-world problems, and crafting scalable and effective ML/AI ...

phData

OR

We are looking for a Principal Solutions Architect to join our Machine Learning team. In this role ... MLOps. * Mentor and guide ML engineers, data scientists, and other team members to elevate the ...

Cresta

OR · On-site

$104K - $143K/yr

About the role We are looking for a Senior Machine Learning Engineer, Voice Experience to help build the next generation of AI-powered voice systems for the contact center. In this role, you will ...

Nextdoor

OR

$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 ...

Instacart

OR · On-site

Strong programming (Python, Golang) and algorithmic skills. * Solid foundations in machine learning, algorithms, or optimization * Curious, self-motivated, and comfortable working on open-ended ...

Logistics Management Institute

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 ...

Instacart

OR · On-site

$91K - $124K/yr

Overview As a Senior Machine Learning Engineer II on the Ads Response Prediction team, you will ... The team has strong ML infrastructure and MLOps support, including Delta/DBT-Spark data pipelines ...

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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.

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.

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 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
Senior Machine Learning Engineer, Operations Research

Senior Machine Learning Engineer, Operations Research

Instacart

OR • Remote

$204K/yr

Other

Posted 4 days ago

Instacart rating

7.1

Company rating: 7.1 out of 10

Based on 31 frontline employees who took The Breakroom Quiz

29th of 63 rated delivery companies

Job description

Overview:

We are looking for a Senior Machine Learning Engineer with a strong Operations Research background to join the Service Availability & Routing team within Instacart's Logistics organization. In this role, you will work at the intersection of combinatorial optimization, mathematical programming, and AI to solve high-impact problems in the fulfillment space - including order batching, shopper routing, service availability prediction, and real-time assignment. You'll partner closely with engineering, product, and data science to ship models and algorithms that directly influence Instacart's profitability and shopper experience at scale.

The Logistics & ML group is responsible for the intelligence and execution behind Instacart's fulfillment system. The team optimizes a multi-sided marketplace to ensure customers get their orders on-time and in high quality, shoppers get efficient and fulfilling work, and retailers and consumer brands get reasonable business. The team tackles hard problems in a variety of spaces, such as matching, pricing, and geospatial, as well as foundational problems executing on a high throughput system with dynamic data.

About the Job:

  • Design, develop, and deploy machine learning solutions to tackle practical challenges in the marketplace.
  • Collaborate closely with product managers, data scientists, and backend engineers to deeply understand business needs and create impactful ML applications.
  • Actively engage with diverse stakeholders to ensure that solutions are well-integrated and aligned with business goals.
  • Push the envelope on our operational efficiency by continually refining and advancing our algorithms and models.


About You:

Minimum Qualifications:

  • Have a graduate degree (masters or PhD) in Operations Research or Industrial Engineering
  • 3+ years of industry experience using machine learning to solve real-world problems with large datasets
  • Have strong programming skills in Python and fluency in data manipulation (SQL, Pandas) and Machine Learning (scikit-learn, XGBoost, Keras/Tensorflow) tools
  • Have strong analytical skills and problem-solving ability
  • Are a strong communicator who can collaborate with diverse stakeholders across all levels

Preferred Qualifications:

  • Knowledge of deep learning frameworks and methodologies
  • Experience in applying machine learning and optimization techniques to solve marketplace problems


#LI-Remote

What Instacart employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Instacart

Sourced by ZipRecruiter

Instacart, based in San Francisco, CA, US, operates within the retail industry, specifically grocery delivery and pick-up service. It is recognized as a pioneer in this field, delivering fresh groceries from local stores directly to customers' doors. The company, which launched its services in 2012, continues to pioneer change in the online grocery shopping sector through its commitment to cutting-edge technology, new business ideas, and dedicated service.

Industry

Technology, communication and media

Company size

10,000+ Employees

Headquarters location

San Francisco, CA, US

Year founded

2012

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