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Data Curation Ai Machine Learning Jobs in Oregon

Machine Learning Principal Solutions Architect

OR ยท On-site +1

  • Dental

  • Vision

  • Retirement

  • PTO

We are looking for a Principal Solutions Architect to join our Machine Learning team. In this role ... Own and drive end-to-end solution design and delivery of AI/ML and data solutions for strategic ...

Applied AI Solutions Architect

OR ยท On-site +1

$63 - $83/hr

  • Dental

  • Vision

  • Retirement

  • PTO

Required Qualifications Experience * 8+ years of experience designing, building, or delivering Data, Analytics, Cloud, Software, Machine Learning, or AI solutions, including at least 5 years ...

AI & GenAI Data Scientist-Director

Portland, OR ยท On-site

$155K - $410K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Responsibilities - Leading the design and development of AI and Machine Learning solutions to transform raw data into actionable insights - Overseeing the implementation of data infrastructure and ...

AI/ML Data Engineer

$117K - $140K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Operationalize forecasting and machine learning models through repeatable training, evaluation ... Partner with Data Engineering and BI teams to ensure forecast outputs, KPIs, business logic, and AI ...

General Information

Portland, OR ยท On-site

$91K - $115K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

You'll support clients who are adopting or scaling AI solutions, including generative AI, machine learning platforms, AI-enabled applications, data platforms, and cloud-native services. Your work ...

Sr. Machine Learning Engineer

Hillsboro, OR ยท On-site

$113K - $156K/yr

  • Medical

  • Retirement

  • PTO

... machine (AI PC, edge, on-prem, and beyond), keeping data private and token costs low, while ... Machine Learning Engineer / Data Scientist** to join our team, working on agent harness research ...

Showing results 41-60

Data Curation Ai Machine Learning information

What are the key skills and qualifications needed to thrive as a data curation AI machine learning specialist?

To thrive as a Data Curation AI Machine Learning Specialist, you need strong data management skills, a background in computer science or data science, and experience with machine learning principles. Familiarity with programming languages like Python or R, data labeling tools, and database systems, as well as certifications in machine learning or data engineering, are typically required. Attention to detail, critical thinking, and effective communication stand out as essential soft skills for managing complex datasets and collaborating with cross-functional teams. These skills ensure high-quality, well-organized data that drives accurate machine learning models and reliable AI outcomes.

What is a data curation AI machine learning specialist?

A Data Curation AI/Machine Learning specialist is a professional who manages, organizes, and prepares large datasets to be used in artificial intelligence and machine learning projects. They ensure that data is accurate, relevant, and accessible, often cleaning and labeling data so it can be effectively used to train machine learning models. Their role bridges the gap between raw data sources and the teams building AI solutions, enabling more reliable and efficient model development. They may also work with data governance, privacy, and compliance issues to ensure data quality and security.

What are some common challenges faced by data curation professionals working in AI and machine learning projects?

One of the key challenges data curation specialists encounter in AI and machine learning is ensuring the quality and consistency of large, diverse datasets. This often involves dealing with missing, incomplete, or biased data, which can impact model performance. Additionally, data curators must navigate evolving data privacy regulations and work closely with data scientists, engineers, and domain experts to align data preparation with project goals. Effective communication and a meticulous approach are crucial for maintaining data integrity and supporting robust machine learning outcomes.

What is the difference between Data Curation Ai Machine Learning vs Data Analyst?

AspectData Curation Ai Machine LearningData Analyst
Primary FocusPreparing and managing data for AI and ML modelsAnalyzing data to generate business insights
Skills RequiredData management, programming, understanding of AI/ML algorithmsStatistical analysis, data visualization, Excel, SQL
Tools UsedPython, R, SQL, data cleaning toolsExcel, Tableau, SQL, statistical software
Work EnvironmentData science teams, AI/ML projects, tech companiesBusiness departments, analytics teams, consulting firms

While Data Curation Ai Machine Learning specialists focus on preparing data for AI and machine learning models, Data Analysts interpret data to support business decisions. Both roles require strong data skills but differ in their primary objectives and tools used.

What are popular job titles related to Data Curation Ai Machine Learning jobs in Oregon?

For Data Curation Ai Machine Learning jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Data Curation Ai Machine Learning jobs in Oregon look for?

The top searched job categories for Data Curation Ai Machine Learning jobs in Oregon are:

What cities in Oregon are hiring for Data Curation Ai Machine Learning jobs?

Cities in Oregon with the most Data Curation Ai Machine Learning job openings:

Machine Learning Principal Solutions Architect

phData

OR โ€ข On-site, Remote

Full-time

Dental, Vision, Retirement, PTO

Re-posted 10 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)