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Freelance Machine Learning Engineer Jobs in Oregon

Principal Machine Learning Engineer, Agentic AI

OR · On-site +1

$204.40K - $326.60K/yr

About the role As a Principal Machine Learning Engineer on the Agentic Artificial Intelligence team, you will get to: * Develop large-scale, fault-tolerant multimodal agentic experiences that reach ...

OR

$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 ...

OR

$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 ...

OR

$170K - $334K/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

$523K - $920K/yr

The Localization Data Science and Engineering team is at the forefront of removing language ... We are seeking an experienced Machine Learning leader to lead a team of Research Scientists and ...

OR · On-site

We value curiosity, experimentation, and a commitment to continuous learning. What will you do? As an AI Software Engineering Intern, you will own an end-to-end project from idea to functioning ...

... Engineering, Mathematics, or a related field. * 5+/4+ years of professional work experience after BS/MS applying machine learning to real-world problems, and crafting scalable and effective ML/AI ...

Senior Machine Learning Test Engineer

OR · On-site +1

$110.40K - $143.40K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East Coast Position Overview As a Senior Machine Learning Test Engineer in the Research Enablement team ...

OR · On-site

Strong Python programming skills * Familiarity with containers, numeric libraries, modular software design * Deep knowledge of state-of-the-art DNN architectures and machine learning techniques and ...

Technical Architect - Machine Learning

OR · Remote

$66.25 - $80/hr

Quantiphi is an award-winning, AI-First digital engineering and consulting company focused on ... Role: Architect - Machine Learning Experience Level: 7+ years Employment type: Full Time Location:

OR · On-site

$66.25 - $80/hr

Quantiphi is an award-winning, AI-First digital engineering and consulting company focused on ... Technical Architect Machine Learning Engineer - Agentic AI & Multi-Agent Systems Experience Level ...

OR

$104.40K - $143.40K/yr

GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve ... We are now looking for an extraordinary Senior Perception Engineer to develop and productize NVIDIA ...

We are looking for a Principal Solutions Architect to join our Machine Learning team. In this role ... You will collaborate closely with clients, Sales, data scientists, ML engineers, and platform teams ...

OR

$523K - $920K/yr

The Localization Data Science and Engineering team is at the forefront of removing language ... We are seeking an experienced Machine Learning leader to lead a team of Research Scientists and ...

We're looking for a passionate and talented Software Engineer for Machine Learning to join our Algorithms team. In this role, you will apply your expertise in software engineering to design, develop ...

OR · On-site

$91.40K - $124.90K/yr

Overview As a Senior Machine Learning Engineer II on the Ads Response Prediction team, you will lead the design and development of core ML models that power Instacart's ads ecosystem. This is a ...

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Freelance Machine Learning Engineer information

See Oregon salary details

$15

$50

$139

How much do freelance machine learning engineer jobs pay per hour?

As of May 30, 2026, the average hourly pay for freelance machine learning engineer in Oregon is $50.44, according to ZipRecruiter salary data. Most workers in this role earn between $25.67 and $65.34 per hour, depending on experience, location, and employer.

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

To thrive as a Freelance Machine Learning Engineer, you need expertise in programming (especially Python), a solid grasp of machine learning algorithms, and a relevant academic background such as a degree in computer science, mathematics, or engineering. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (AWS, GCP, Azure), and experience with version control systems are typically required. Strong problem-solving, self-management, and client communication skills help set successful freelancers apart. These competencies are crucial for delivering effective solutions, managing projects independently, and building client trust in a competitive market.

How do freelance machine learning engineers typically manage client expectations and project scopes?

Freelance machine learning engineers often work with clients who may not have a deep technical understanding of AI or data science. A common challenge is clearly defining the project scope and deliverables at the outset, ensuring both parties understand what is feasible given the data, time, and budget constraints. Successful freelancers use regular progress updates, milestone-based deliverables, and transparent communication to manage expectations and avoid scope creep. Building trust through clear documentation and setting realistic timelines also helps foster long-term client relationships.

What does a Freelance Machine Learning Engineer do?

A Freelance Machine Learning Engineer designs, develops, and implements machine learning models and algorithms for clients on a project basis. They work independently to analyze data, build predictive models, and help businesses solve complex problems using AI and machine learning techniques. Their responsibilities may also include data preprocessing, model evaluation, and deploying solutions into production environments. Freelance Machine Learning Engineers often collaborate remotely with teams and must manage their own schedules and client relationships.

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

AspectFreelance Machine Learning EngineerData Scientist
CredentialsTypically requires a degree in computer science, data science, or related fields; certifications in machine learning or AI are a plusUsually holds a degree in statistics, data science, or related areas; certifications in data analysis or visualization are common
Work EnvironmentIndependent, project-based work often remotely for various clientsOften employed full-time in organizations or consulting roles, sometimes freelance
Industry UsageUsed across tech, finance, healthcare, and startups for deploying ML modelsApplied in research, analytics, and strategic decision-making across industries

Freelance Machine Learning Engineers focus on developing and deploying ML models independently for diverse clients, while Data Scientists analyze data to extract insights, often working within organizations. Both roles require strong technical skills, but their work scope and environment differ significantly.

What are the most commonly searched types of Machine Learning Engineer jobs in Oregon? The most popular types of Machine Learning Engineer jobs in Oregon are:
What are popular job titles related to Freelance Machine Learning Engineer jobs in Oregon? For Freelance Machine Learning Engineer jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Freelance Machine Learning Engineer jobs in Oregon look for? The top searched job categories for Freelance Machine Learning Engineer jobs in Oregon are:
What cities in Oregon are hiring for Freelance Machine Learning Engineer jobs? Cities in Oregon with the most Freelance Machine Learning Engineer job openings:
Infographic showing various Freelance Machine Learning Engineer job openings in Oregon as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $104,915 per year, or $50.4 per hour.
Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Capital One

On-site, Remote

$104.40K - $143.40K/yr

Full-time

Posted 22 days ago


Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 134 frontline employees who took The Breakroom Quiz

74th of 141 rated banks


Job description

Sr. Distinguished Machine Learning Engineer (Remote-Eligible)

Overview:

At Capital One, we are creating responsible and reliable AI systems, changing banking for good. For years, Capital One has been an industry leader in using machine learning to create real-time, personalized customer experiences. Our investments in technology infrastructure and world-class talent - along with our deep experience in machine learning - position us to be at the forefront of enterprises leveraging AI. From informing customers about unusual charges to answering their questions in real time, our applications of AI & ML are bringing humanity and simplicity to banking. We are committed to continuing to build world-class applied science and engineering teams to deliver our industry leading capabilities with breakthrough product experiences and scalable, high-performance AI infrastructure. At Capital One, you will help bring the transformative power of emerging AI capabilities to reimagine how we serve our customers and businesses who have come to love the products and services we build.

Team Description:

The Consumer Engagement Platform organization at Capital One empowers rapid financial product innovation at scale and delivers developer joy, for all Capital One's consumer products and organizations, by providing well-managed, self-service, experimentation-driven, and personalized product development vehicles. Hyper Personalization org is building the intelligence and infrastructure that will enable Capital One to deliver truly individualized, real-time customer experiences at scale - turning every channel into a context-aware decisioning surface, from home feeds to marketing and servicing messages. The org's mission is to move Capital One to deliver always-on, cohort-of-one personalization, powered by resilient data foundations, production-grade ML and GenAI systems, and low-latency application platforms that make it easy for teams across the company to experiment, innovate, and serve the right experience to every customer at the right moment.

What you'll do in the role:

  • Define and drive technical strategy and roadmap for our Personalization Platform that powers real-time, personalized product experiences and multi-channel targeted user messaging across all Capital One products and services.

  • Partner cross-functionally with Product, Data science, Cloud infrastructure, and Machine learning platform teams to align on and co-develop the advanced recommendation systems and algorithms serving our Capital One users.

  • Develop and maintain a flexible, scalable rules engine to enable business-driven personalization logic, allowing dynamic configuration of user segmentation, targeting rules, and real-time decisioning while integrating seamlessly with ML-driven recommendations.

  • Design, build and maintain robust ML infrastructure and pipelines to support end-to-end workflows including feature extraction, model training, testing, guardrails, model evaluation, deployment, and both real-time and batch inference - ensuring high performance, scalability, and reliability.

  • Architect low-latency, event-driven systems for enabling real-time dynamic personalization and decisioning based on streaming data, user behavior, and contextual signals.

  • Drive the evolution of MLOps practices by building automated metrics-backed deployment workflows, integration validation and testing systems, and scalable monitoring & observability.

  • Invent and introduce state-of-the-art LLM optimization techniques to improve the performance - scalability, cost, latency, throughput - of large scale production AI systems.

  • Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more.

  • Provide organizational technical leadership to influence architecture, engineering standards, cross-team strategies, mentoring engineers and driving organization wide platform innovation.

The Ideal Candidate:

  • You love to build systems, take pride in the quality of your work, and also share our passion to do the right thing. You want to work on problems that will help change banking for good.

  • Passion for staying abreast of the latest research, and an ability to intuitively understand scientific publications and judiciously apply novel techniques in production.

  • You adapt quickly and thrive on bringing clarity to big, undefined problems. You love asking questions and digging deep to uncover the root of problems and can articulate your findings concisely with clarity. You have the courage to share new ideas even when they are unproven.

  • You are deeply Technical. You possess a strong foundation in engineering and mathematics, and your expertise in hardware, software, and AI enable you to see and exploit optimization opportunities that others miss.

  • You are a resilient trail blazer who can forge new paths to achieve business goals when the route is unknown.

Capital One is open to hiring a Remote Employee for this opportunity

Basic Qualifications:

  • Bachelor's degree

  • At least 10 years of experience designing and building data-intensive solutions using distributed computing

  • At least 7 years of experience programming in C, C++, Python, or Scala

  • At least 4 years of experience with the full ML development lifecycle using modern technology in a business critical setting

Preferred Qualifications:

  • 8+ years of experience deploying scalable, responsible AI solutions on major cloud platforms (AWS, GCP, Azure); Master's or PhD in Computer Science or a relevant technical field.

  • 5+ years of proven expertise in designing, implementing and scaling personalization platform and recommendation systems serving one or more areas of Feed Personalization/Ads Ranking/Targeted Marketing Messaging.

  • 5+ years of strong proficiency in Python, Java, C++, or Golang; hands-on experience with ML frameworks (PyTorch, TensorFlow) and orchestration tools (Databricks, Airflow, Kubeflow).

  • 5+ years of experience developing and applying state-of-the-art techniques for optimizing training and inference systems to improve hardware utilization, latency, throughput, and cost.

  • 5+ years of deep expertise in cloud-native engineering, containerization (Docker, Kubernetes), and automated CI/CD deployment.

  • Passion for staying on top of the latest AI research and AI systems, and judiciously apply novel techniques in production

  • Excellent communication and presentation skills, with the ability to articulate complex AI concepts to peers

  • Proven leadership in driving platform strategy, fostering cross-functional collaboration, and influencing technical direction across the company.

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Remote (Regardless of Location): $286,200 - $326,700 for Sr Distinguished Machine Learning Engineer


McLean, VA: $314,800 - $359,300 for Sr Distinguished Machine Learning Engineer










Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).


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