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Machine Learning Jobs in Oregon (NOW HIRING)

OR · On-site

We are looking for a Principal Solutions Architect to join our Machine Learning team. In this role, you will lead the architecture, implementation, and lifecycle management of AI/ML applications that ...

OR · On-site

$122K - $161K/yr

... machine learning to real-world problems, and crafting scalable and effective ML/AI solutions. * Strong domain knowledge in at least one of the following: RAG, LLM, information retrieval, Multimodal ...

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 ...

OR

$466K - $750K/yr

We work at the intersection of creative game design and cutting-edge machine learning, ensuring that dynamic storytelling is not only novel but also coherent, immersive, and safe for our players. We ...

Senior Staff Machine Learning Scientist, Assets

OR · On-site +1

$91K - $124K/yr

We're looking for a Senior Staff Machine Learning Scientist to help us solve challenging problems to address emerging customer needs and behaviors. The ideal candidate can move fast but with high ...

Natera is seeking a Staff Machine Learning Scientist - Agentic AI to join our AI team, an advanced R&D and core AI innovation team bridging the gap between molecular discovery and clinical execution.

$125K - $172K/yr

Overview We are looking for a Senior Principal Machine Learning Engineer to lead the design and delivery of end-to-end ML/AI systems that turn vast volumes of claims, clinical, and member data into ...

OR · On-site

$55.75 - $73.75/hr

Senior Machine Learning Engineer, Data & Intelligence Products AcuityMD is a software and data platform that accelerates access to medical technologies. We help MedTech companies understand how their ...

You will build the machine learning models that augment our simulation-based engine for predicting campaign delivery - turning a slow, rules-based simulation into fast, accurate, learnable models of ...

OR

$466K - $750K/yr

Design and implement machine learning and optimization algorithms to improve ad quality and performance. Build, train, and evaluate models on large-scale production data. Develop online and offline ...

We are looking for a Machine Learning Scientist 6 to serve as a vertical technical lead across our core Live Ads ML problem areas - forecasting, targeting and personalization, bidding and pacing ...

We are looking for a Machine Learning Scientist 6 to serve as a vertical technical lead across our core Live Ads ML problem areas - forecasting, targeting and personalization, bidding and pacing ...

OR · On-site

$466K - $750K/yr

Design and implement machine learning-driven bidding algorithms that optimize ad performance against objectives such as Clicks, Conversions, CPA and ROAS,. Build, train, and evaluate bidding ...

Numerator is looking for a hands-on Tech Lead Manager to join our growing Machine Learning team. This is a 50/50 player-coach role: you'll directly manage a small team of ML engineers while ...

OR · On-site

$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 ...

Numerator is looking for a hands-on Tech Lead Manager to join our growing Machine Learning team. This is a 50/50 player-coach role: you'll directly manage a small team of ML engineers while ...

OR · On-site

$194K - $310K/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 ...

Master's or PhD in Machine Learning, Computer Science, or a closely related field (or equivalent practical experience). 6+ years of handson ML experience (or 4+ years with a relevant PhD), including ...

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Machine Learning information

See Oregon salary details

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$45K

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How much do machine learning jobs pay per year?

As of Jul 14, 2026, the average yearly pay for machine learning in Oregon is $45,023.00, according to ZipRecruiter salary data. Most workers in this role earn between $34,400.00 and $48,600.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and often working in high-paying industries such as finance or technology, can earn salaries of $500,000 or more annually. Achieving this level typically requires a strong educational background, specialized certifications, and a track record of impactful projects.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in deep learning, data analysis, and programming with tools like Python and TensorFlow. Such roles usually demand extensive experience, a strong educational background, and sometimes leadership responsibilities in developing or deploying AI systems.

What is a Machine Learning job?

A Machine Learning job involves developing algorithms and models that enable computers to learn from data and make predictions or decisions without explicit programming. Professionals in this field work with large datasets, design and train machine learning models, and optimize them for performance and accuracy. Roles often require knowledge of programming languages like Python or R, experience with frameworks like TensorFlow or PyTorch, and an understanding of statistics and data science principles. Machine learning engineers and data scientists collaborate with software developers and domain experts to build AI-driven solutions for various industries.

What are some typical day-to-day responsibilities in a Machine Learning role?

As a machine learning professional, your daily tasks may include data preprocessing, developing and training models, evaluating performance metrics, and experimenting with algorithms to optimize results. You’ll often collaborate closely with data scientists, software engineers, and business stakeholders to align technical solutions with organizational goals. Regular activities can also involve deploying models to production, monitoring performance, and troubleshooting any issues that arise post-deployment. Staying up to date with recent ML research and participating in team discussions or code reviews are also common parts of the job.

What jobs can I get with machine learning?

With machine learning skills, you can pursue roles such as machine learning engineer, data scientist, AI researcher, or data analyst. These positions typically require knowledge of programming languages like Python or R, experience with machine learning frameworks, and strong analytical skills. They are found across industries including technology, finance, healthcare, and automotive sectors.

What are the key skills and qualifications needed to thrive in the Machine Learning position, and why are they important?

To thrive in Machine Learning, you need a solid background in mathematics, statistics, programming (especially Python or R), and a formal degree in computer science, data science, or a related field. Experience with popular ML frameworks (such as TensorFlow, PyTorch, or Scikit-learn), version control, and relevant certifications like AWS Certified Machine Learning are highly valued. Strong problem-solving skills, curiosity, clear communication, and the ability to work both independently and within multidisciplinary teams make candidates stand out. These skills and qualities are essential for developing robust models, staying updated with technology advancements, and collaborating effectively on complex projects.

Which 3 jobs will survive AI?

Machine Learning roles such as data scientists, AI specialists, and machine learning engineers are expected to persist as AI advances, due to their need for complex problem-solving, domain expertise, and ongoing model development. These jobs require advanced skills in programming, statistics, and understanding of AI tools, making them less susceptible to automation. Continuous learning and staying updated with new algorithms and frameworks are essential for these positions.
What are the most commonly searched types of Machine Learning jobs in Oregon? The most popular types of Machine Learning jobs in Oregon are:
What are popular job titles related to Machine Learning jobs in Oregon? For Machine Learning jobs in Oregon, the most frequently searched job titles are:
What cities in Oregon are hiring for Machine Learning jobs? Cities in Oregon with the most Machine Learning job openings:
Machine Learning Principal Solutions Architect

Machine Learning Principal Solutions Architect

phData

OR • On-site

Other

Dental, Vision, Retirement, PTO

Re-posted 8 days ago


Job description

We are looking for a Principal Solutions Architect to join our Machine Learning team. In this role, you will lead the architecture, implementation, and lifecycle management of AI/ML applications that deliver measurable business value for our clients. You will take full ownership of strategic AI/ML projects from vision and solution design through deployment and ongoing optimization while ensuring that models can be trained, tuned, and operated reliably using client data. You will collaborate closely with clients, Sales, data scientists, ML engineers, and platform teams to deliver high-quality solutions and advance phData's delivery excellence.

Key ResponsibilitiesClient Delivery
  • Own and drive end-to-end solution design and delivery of AI/ML and data solutions for strategic client accounts, from model inference, retraining, and monitoring through to production operations.
  • Translate business and data science requirements into scalable, secure, and resilient architectures that align with phData methodologies, standards, and best practices.
  • Design and create environments for data scientists to build, train, test, and tune AI/ML models and applications using relevant client data.
  • Work within customer systems to extract data from a variety of sources and place it within analytical environments to support model development, training, and tuning.
  • Define deployment approaches and production infrastructure for AI/ML models and applications, ensuring that businesses can reliably consume and maintain the solutions we deliver.
  • Demonstrate the business value of data by partnering with data scientists to manipulate and transform data into actionable insights and deployable machine learning models.
  • Create and execute operational testing strategies, including QA validation, performance testing, and implementation plans to support testing and deployment of AI/ML solutions.
  • Ensure the quality, reliability, and observability of delivered solutions through rigorous testing, documentation, and monitoring.
Collaboration & Leadership
  • Collaborate with cross-functional partners including data scientists, ML engineers, data engineers, platform/DevOps, and business stakeholders to deliver successful client engagements.
  • Provide technical and strategic leadership during workshops, discovery sessions, architecture and design reviews, and project delivery.
  • Partner closely with Sales and account leadership to drive account expansion, identify new opportunities, and ensure long-term client value on strategic accounts.
  • Take full ownership of client success within AI/ML projects, including planning and vision-crafting, managing client expectations, and handling escalations in a proactive and outcome-oriented manner.
  • Ensure high quality in deliverables through code reviews, documentation, testing, governance, and adherence to security and compliance standards.
  • Serve as a visible technical leader and point of escalation for complex AI/ML challenges within key customer engagements.
Practice & Firm Contribution
  • Contribute to internal initiatives such as IP development, accelerators, reference architectures, templates, and playbooks focused on AI/ML and MLOps.
  • Mentor and guide ML engineers, data scientists, and other team members to elevate the overall technical and consulting capabilities of the practice.
  • Represent phData with professionalism in all interactions, communicating clearly with both technical and non-technical stakeholders.
Additional Responsibilities
  • Act as a trusted advisor to senior and executive client stakeholders, shaping AI/ML roadmaps, influencing strategic decisions, and guiding long-term initiatives.
  • Lead multiple work streams concurrently, ensuring alignment across technical teams, business stakeholders, and account leadership.
  • Help define and refine practice standards, reusable assets, and delivery frameworks that improve consistency, quality, and scalability of AI/ML engagements.
  • Champion a culture of customer obsession, continually seeking ways to increase client impact and satisfaction.
About You

You are a customer-obsessed technical leader and consultant who enjoys solving complex data and AI/ML challenges while building trusted relationships with clients. You are equally comfortable discussing architecture with executives and diving deep into code, infrastructure, and data pipelines with engineering teams. You thrive in an outcomes-driven environment, manage multiple work streams with ease, and bring a blend of strong engineering skills, strategic thinking, and excellent communication to every engagement.

Required QualificationsExperience
  • 10+ years of experience as a Machine Learning Engineer, Software Engineer, Data Engineer, or Data Scientist building and deploying production data and machine learning solutions.

Technical / Functional Skills

  • Expertise in modern programming languages such as Python, Scala, Java, or similar, including experience developing APIs and web server applications using frameworks such as Flask, Django, or Spring.
  • Ability to build and operate robust data pipelines using a variety of data sources, programming languages, and toolsets, with strong working knowledge of SQL and the ability to write, debug, and optimize complex and distributed queries.
  • Hands-on experience with big data and analytics ecosystem technologies such as Spark, Snowflake, Databricks, Redshift, Amazon EMR, HDFS, or similar platforms.
  • Familiarity with multiple data source systems such as JMS, Kafka, RDBMS, data warehouses, MySQL, Oracle, and SAP.
  • Systems-level knowledge of network and cloud architecture, Linux-based operating systems, and storage/compute platforms (e.g., AWS, Databricks, Cloudera).
  • Proven experience deploying machine learning models into production environments and ensuring their performance, security, scalability, and reliability.
  • Complete software development lifecycle experience, including design, documentation, implementation, testing, deployment, and ongoing operations.
  • Excellent communication and presentation skills, with prior experience working directly with internal or external customers.
Consulting / Delivery Skills
  • Owning pre-sales and project scoping responsibilities
  • Proven Account Growth / Revenue Generation experience for external clients
  • Experience delivering projects for external or internal clients in a professional services, product, or consulting environment.
  • Ability to break down complex, ambiguous problems into structured, actionable steps and drive them through to completion.
  • Strong written and verbal communication skills in English, with the ability to present technical concepts to both technical and non-technical audiences.
  • Demonstrated customer obsession and a strong desire to make clients successful.
Collaboration & Ownership
  • Demonstrated ability to work effectively with distributed and cross-functional teams, including Sales, data scientists, ML engineers, data engineers, and business stakeholders.
  • Proven track record of taking ownership of client outcomes, managing multiple priorities and work streams, and delivering high-quality work with minimal supervision.
  • Comfort operating in client environments, quickly learning new systems and tools, and adapting solutions to fit existing architectures and processes.
Education
  • Bachelor's level degree in Computer Science or a related technical field, or equivalent practical experience preferred.
Preferred Qualifications

Preferred qualifications help candidates stand out but are not required for success in this role.

  • A Master's or other advanced degree in data science, computer science, or a related field.
  • Hands-on experience with cloud and data ecosystem technologies such as Spark, Databricks, Snowflake, AWS, Azure, or GCP.
  • Experience working with data science and machine learning libraries and frameworks such as H2O, TensorFlow, Keras, scikit-learn, or similar.
  • Experience with containerization and orchestration technologies such as Docker and Kubernetes.
  • Experience with MLOps tooling such as AWS SageMaker, Azure ML, and MLflow, and with building enterprise-scale ML models.
  • Prior experience in a consulting role or working closely with clients on strategic data and AI/ML initiatives.
  • Relevant side projects such as contributions to open source technology stacks, technical communities, speaking, or writing.
Location & Time Zone Expectations

This role is based in the United States and operates primarily in the Central Time Zone.

  • We are a remote-first company, and you should be comfortable working with a distributed global team.
  • Some flexibility may be required to collaborate across time zones with colleagues and clients.
  • Client needs may occasionally require flexibility in working hours to support key milestones or workshops.
Why phData?
  • Impactful Work: Partner with leading organizations on meaningful data & AI initiatives.
  • Collaborative Culture: Work with a supportive, high-performing global team that values transparency, autonomy, and continuous improvement.
  • Growth Opportunities: Access to challenging projects, mentorship, and structured development pathways.

Values-Driven: We prioritize doing the right thing for our clients, our teams, and our community.

Benefits at phData

US:

  • Remote-First Work Environment
  • 401k plan with company match
  • Dental and Vision insurance
  • Home Office Equipment Stipend
  • Annual stipend for Learning and Development
  • Competitive comp, excellent benefits, 4 weeks PTO plan plus 10 Holidays (and other cool perks)