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Senior Machine Learning Researcher Jobs in Oregon

OR · On-site

We are looking for a Principal Solutions Architect to join our Machine Learning team. In this role ... Act as a trusted advisor to senior and executive client stakeholders, shaping AI/ML roadmaps ...

OR

$466K - $750K/yr

Applied Machine Learning Research at Netflix drives various aspects of our business, including personalization, recommendations, search, content understanding, messaging, targeting, new member ...

... Research covering Advanced Statistics, Machine learning and AI. * Experience with the latest ... senior #LI-LL1 #remote Employment Type: OTHER

... Research covering Advanced Statistics, Machine learning and AI. * Experience with the latest ... Senior #LI-LL1 Employment Type: OTHER

Applied Scientist

OR · On-site +1

The team conducts machine learning research, evaluates model performance, and partners closely with engineering teams to translate promising ideas into scalable model improvements. As an Applied ...

... Research covering Advanced Statistics, Machine learning and AI. * Experience with the latest ... senior Employment Type: OTHER

... Research covering Advanced Statistics, Machine learning and AI. * Experience with the latest ... senior #LI-LL1 Employment Type: OTHER

The role will involve working with other Senior Data Scientists and mentoring Associate Data ... machine learning and analytics research to production. On any given day, you will have the ...

Senior Data Scientist

OR · On-site +1

$140K - $190K/yr

In this position, you will drive the development of statistical models and machine learning ... the clinical research community. What You'll Be Working On * Site Randomization Forecasting:

... senior staff-level scope and impact. Deep knowledge of machine learning, optimization, and data ... analysis techniques. Experience in ad optimization stack, e.g. targeting, ranking, bidding.

OR

$466K - $750K/yr

You will work closely with our machine learning researchers, product managers, and other engineers to come up with new systems, improve existing ones, and enable offline experiments and A/B tests.

Senior Software Engineer

Beaverton, OR · On-site

$127K - $168K/yr

... machine learning models to support prediction and optimization use cases; operationalize machine learning models as scalable APIs or batch inference services; implement and maintain CI/CD pipelines ...

Showing results 41-60

Senior Machine Learning Researcher information

What opportunities for collaboration typically exist for senior machine learning researchers within a company?

Senior Machine Learning Researchers frequently collaborate with cross-functional teams, including data engineers, software developers, and domain experts. This collaboration ensures that research insights are effectively translated into scalable solutions and integrated into products or services. Researchers often participate in brainstorming sessions, code reviews, and joint publications, fostering a culture of innovation and shared knowledge. These interactions not only drive the success of projects but also provide valuable learning experiences and networking opportunities.

What does a senior machine learning researcher do?

A Senior Machine Learning Researcher leads the development and application of advanced machine learning models to solve complex problems. They are responsible for designing experiments, analyzing large datasets, publishing research findings, and collaborating with engineering teams to implement solutions. Additionally, they mentor junior researchers, stay updated with the latest advancements in AI, and often contribute to setting the research agenda for their organization.

What is the difference between Senior Machine Learning Researcher vs Data Scientist?

AspectSenior Machine Learning ResearcherData Scientist
CredentialsAdvanced degrees in CS, ML, or related fieldsDegree in CS, statistics, or related fields; certifications optional
Work EnvironmentResearch labs, R&D teams, academiaBusiness analytics, product teams, startups
Industry UsageResearch-focused roles in tech, academia, R&DData analysis, business insights, product development
Search & Comparison IntentUnderstanding research vs applied roles in MLExploring data analysis careers and skills

While both roles involve working with data and machine learning, a Senior Machine Learning Researcher primarily focuses on developing new algorithms and advancing ML theory in research settings. In contrast, a Data Scientist applies existing models to analyze data, generate insights, and support business decisions. The roles differ mainly in their focus—research innovation versus practical application—though they share overlapping skills and credentials.

What are the key skills and qualifications needed to thrive as a senior machine learning researcher, and why are they important?

To thrive as a Senior Machine Learning Researcher, you need advanced knowledge in machine learning algorithms, statistical analysis, programming (typically in Python), and a relevant advanced degree such as a PhD or Master's in computer science or a related field. Experience with frameworks like TensorFlow or PyTorch, as well as familiarity with cloud computing platforms and research publication, is often required. Strong problem-solving, collaboration, and communication skills help you work effectively with cross-functional teams and present complex ideas clearly. These skills and qualities are essential for driving innovation, developing robust models, and translating research into practical, impactful solutions.
What are popular job titles related to Senior Machine Learning Researcher jobs in Oregon? For Senior Machine Learning Researcher jobs in Oregon, the most frequently searched job titles are:
What cities in Oregon are hiring for Senior Machine Learning Researcher jobs? Cities in Oregon with the most Senior Machine Learning Researcher job openings:
Infographic showing various Senior Machine Learning Researcher job openings in Oregon as of June 2026, with employment types broken down into 2% As Needed, 49% Full Time, 47% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

Machine Learning Principal Solutions Architect

phData

OR • On-site

Full-time

Dental, Vision, Retirement, PTO

Re-posted 6 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)