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Mlops Machine Learning Engineer Jobs in Oregon (NOW HIRING)

OR · On-site

$66.25 - $80/hr

Quantiphi is an award-winning, AI-First digital engineering and consulting company focused on ... You will implement best-in-class MLOps practices for monitoring, continuous integration/continuous ...

As a Principal Machine Learning Engineer on the Agentic AI team, you will: * Leverage frameworks like AgentSDK, and LangChain/LangGraph to design, prototype, and develop multi-agent systems that are ...

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 ...

OR

$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 ...

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 ...

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 ...

OR · On-site

As an AI/Machine Learning Engineer Intern , you will be tasked with applying software engineering skills to create reliable, AI-powered products within a fast-paced product engineering environment.

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

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Mlops Machine Learning Engineer information

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 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:
Entry-Level Machine Learning Engineer

Entry-Level Machine Learning Engineer

SynergisticIT

Eugene, OR

Other

Posted 14 days ago


Job description

Are you passionate about coding or technology and ready to make your mark in tech? For more than 15 years, SynergisticIT has been helping aspiring developers like you excel in the tech industry. We focus on equipping you with the skills and experience needed to not only secure a job but to thrive in your career!
Why Partner with SynergisticIT?

  • Customized inputs to achieve the desired output :designed with industry needs in mind, ensuring you're equipped with the most sought-after skills.
  • Exclusive Opportunities: Our extensive network allows you to connect with leading tech firms.
  • Outstanding Outcomes: Many of our candidates land multiple job offers, often with starting salaries of $100k or more!

https://www.synergisticit.com/candidate-outcomes/
https://synergisticit.wistia.com/medias/o5gmv7i9eu
https://www.youtube.com/playlist?list=PLJgkOBQ51j5AHT5I6n29glr0q6trzkxYD
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Why do Tech Companies not Hire recent Computer Science Graduates | SynergisticIT
Technical Skills or Experience? | Which one is important to get a Job? | SynergisticIT
Who Should Apply? We're looking for recent grads in Mathematics, Statistics , Computer Science or Engineering or candidates with gaps in their career or people wanting to switch careers into tech. SynergisticIT is committed to supporting your journey!
Preferred SKILLS For Java /Full stack/Devops Positions
Associate or Bachelors degree or Masters degree in Computer Science, Computer Engineering, Electrical Engineering, Information Systems, IT
Knowledge of Core Java , javascript , C++ or software programming
Spring boot, Microservices, AWS, Docker, Jenkins, Github, Kubernates and REST API's experience
For data Science/Data Engineer, Data Analyst/AI/Machine learning Positions
Preferred SKILLS
Associate or Bachelors degree or Masters degree in Computer Science, Computer Engineering, Electrical Engineering, Information Systems, IT, Statistics, Mathematics or having good logical aptitude
Knowledge of Statistics, Databricks, Snowflake, Pyspark , PowerBI, Tableau, Gen AI, LLM, Sagemaker, Python, Computer Vision, data visualization tools
Candidates lacking technical skills or relevant experience can research our Job Placement Programs which can assist in landing a Job
If you get emails from our Job Placement team and are not interested please email them or ask them to take you off their distribution list and make you unavailable as they share the same database with the client servicing team who only connect with candidates who are matching client requirements.
No phone calls please. Shortlisted candidates would be reached out. No third party or agency candidates or c2c candidates
Embrace Your Future! We also assist with F1 OPT to transition into H1B and Green Card byproviding comprehensive support. All positions are open to candidates of all visa types and US citizens.
Are you ready to make an impact?