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Senior Machine Learning Engineer Jobs in Oregon (NOW HIRING)

Cresta

OR

Machine Learning Engineers at Cresta work across several high-impact AI initiatives. Final team ... Mentor senior engineers, raise the technical bar, and contribute to long-term AI strategy and ...

phData

OR · On-site

You will collaborate closely with clients, data scientists, data engineers, platform/DevOps teams ... Act as a trusted advisor to senior client stakeholders, shaping roadmaps, influencing strategic ...

Instacart

OR

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

Instacart

OR

Partnering with world-class engineers, scientists, and PMs, we build the ranking backbone that ... Develop production-grade Multi-Task Learning (e.g., shared encoders, MMOE/PLE task heads) to ...

Instacart

OR

You will help design and build end-to-end machine learning solutions. * You will be working in ... You will work closely with engineers, product managers, other teams, and both internal and external ...

Instacart

OR · On-site

... data engineering to machine learning & AI to frontend technologies and more. About the Job ... Demonstrated ability to lead technical discussions and collaborate effectively at senior to ...

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All JobsSenior Machine Learning Engineer JobsSenior Machine Learning Engineer Jobs in Oregon

Senior Machine Learning Engineer information

See Oregon salary details

$62.9K

$133.8K

$194K

How much do senior machine learning engineer jobs pay per year?

As of Jun 22, 2026, the average yearly pay for senior machine learning engineer in Oregon is $133,807.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,500.00 and $151,700.00 per year, depending on experience, location, and employer.

What are some common challenges Senior Machine Learning Engineers face when deploying models to production, and how can they be addressed?

Senior Machine Learning Engineers often encounter challenges related to model scalability, maintaining performance in real-world scenarios, and ensuring reliable integration with existing systems. Addressing these challenges typically involves thorough testing, implementing robust monitoring for model drift, and collaborating closely with DevOps and software engineering teams to streamline deployment pipelines. Staying updated on best practices in MLOps and adopting tools for automated deployment and monitoring can greatly improve the reliability and efficiency of production models.

What does a Senior Machine Learning Engineer do?

A Senior Machine Learning Engineer designs, develops, and implements machine learning models to solve complex problems. They are responsible for selecting appropriate algorithms, preprocessing data, and optimizing model performance. Additionally, they collaborate with data scientists, software engineers, and product teams to integrate machine learning solutions into production systems. Senior engineers also mentor junior team members and contribute to setting technical direction for machine learning projects.

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

To thrive as a Senior Machine Learning Engineer, you need advanced knowledge of machine learning algorithms, statistical modeling, and programming languages like Python or Java, typically supported by a degree in computer science or a related field. Experience with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, as well as familiarity with version control and CI/CD systems, is essential. Strong problem-solving, communication, and leadership skills help you collaborate effectively and mentor junior team members. These capabilities are crucial for designing scalable ML solutions and driving impactful results within complex, dynamic projects.

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

AspectSenior Machine Learning EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models in production systemsAnalyzes data, builds models, and provides insights
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

While both roles require strong technical skills and knowledge of machine learning, Senior Machine Learning Engineers focus more on deploying scalable ML solutions in production environments, whereas Data Scientists primarily analyze data and develop models for insights. The roles often overlap but differ in their core responsibilities and focus areas.

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 Senior Machine Learning Engineer jobs in Oregon? For Senior Machine Learning Engineer jobs in Oregon, the most frequently searched job titles are:
What job categories do people searching Senior Machine Learning Engineer jobs in Oregon look for? The top searched job categories for Senior Machine Learning Engineer jobs in Oregon are:
What cities in Oregon are hiring for Senior Machine Learning Engineer jobs? Cities in Oregon with the most Senior Machine Learning Engineer job openings:
Senior Machine Learning Engineer jobs near you
Staff Machine Learning Engineer

Staff Machine Learning Engineer

Cresta

OR

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 22 days ago

Job description

About the role:

Machine Learning Engineers at Cresta work across several high-impact AI initiatives. Final team placement is determined based on experience, strengths, and business needs.

Current focus areas include:

  • Agentic Assist: Lead and build next-generation agentic AI systems that augment contact center agents in real time. This track requires strong pre-LLM ML foundations, deep expertise in LLMs and modern prompting techniques, a rapid prototyping mindset, and a proven ability to translate cutting-edge research into scalable, production-grade systems.
  • Agent & System Quality: Design evaluation frameworks and improve the reliability, robustness, and performance of LLM-powered agents. This includes diagnosing and mitigating failure modes such as hallucinations, retrieval errors, tool misuse, context drift, prompt brittleness, and multi-step reasoning breakdowns, while defining measurable quality metrics (e.g., accuracy, faithfulness, task completion, latency, and cost) for complex, non-deterministic systems.
  • Insights: Architect and scale LLM and retrieval-augmented generation pipelines that ground models in enterprise data. This track focuses on building high-performance ML systems that process complex data, extract structured insights, and deliver real-time, actionable intelligence at scale.

Responsibilities:

  • Define and lead the technical vision for Cresta's next-generation Agentic AI systems, including Agentic Assist and enterprise AI Agents.
  • Architect scalable, production-grade LLM systems that integrate reasoning, retrieval, planning, tool use, and real-time decision-making into cohesive, intelligent workflows.
  • Design and evolve multi-agent orchestration frameworks that combine RAG, structured knowledge, domain-adapted models, and automated actions.
  • Establish best practices for building robust, reliable, and cost-efficient LLM-powered systems in high-scale production environments.
  • Own evaluation strategy for complex, non-deterministic AI systems, including offline benchmarking, online experimentation, LLM-as-a-judge methodologies, and systematic failure analysis.
  • Proactively identify and mitigate agent failure modes such as hallucinations, tool misuse, retrieval errors, prompt brittleness, context drift, and multi-step reasoning breakdowns.
  • Define measurable quality standards (accuracy, faithfulness, task completion, latency, cost efficiency, robustness) and drive continuous system improvement.
  • Influence cross-team architecture decisions across ML, backend, and product engineering to ensure seamless integration of AI capabilities.
  • Mentor senior engineers, raise the technical bar, and contribute to long-term AI strategy and roadmap planning.
  • Translate cutting-edge research advances into practical, high-impact production systems.

Qualifications We Value:

  • Bachelor's degree in Computer Science, Mathematics, or a related field; Master's or Ph.D. strongly preferred.
  • 7+ years of experience building and deploying machine learning systems in production, including deep hands-on experience with LLMs at scale.
  • Demonstrated leadership in architecting complex AI systems, particularly agentic or multi-step LLM workflows.
  • Deep expertise in transformer-based models, embeddings, retrieval systems, and Retrieval-Augmented Generation (RAG) pipelines.
  • Experience designing evaluation frameworks for LLM systems beyond single-turn prompts, including robustness testing and production monitoring.
  • Strong systems thinking: ability to design for scalability, latency constraints, cost efficiency, security, and long-term maintainability.
  • Extensive experience with modern ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) and distributed/cloud-based infrastructure.
  • Proven ability to influence technical direction across teams as a senior individual contributor.
  • A strong bias toward action - able to prototype rapidly while maintaining production rigor.

Perks & Benefits:

We offer a comprehensive and people-first benefits package to support you at work and in life:

  • Comprehensive medical, dental, and vision coverage with plans to fit you and your family
  • Flexible PTO to take the time you need, when you need it
  • Paid parental leave for all new parents welcoming a new child
  • Retirement savings plan to help you plan for the future
  • Remote work setup budget to help you create a productive home office
  • Monthly wellness and communication stipend to keep you connected and balanced
  • In-office meal program and commuter benefits provided for onsite employees

Compensation at Cresta: 

Cresta's approach to compensation is simple: recognize impact, reward excellence, and invest in our people. We offer competitive, location-based pay that reflects the market and what each individual brings to the table.

The posted base salary range represents what we expect to pay for this role in a given location. Final offers are shaped by factors like experience, skills, education, and geography. In addition to base pay, total compensation includes equity and a comprehensive benefits package for you and your family.

OTE Range: $230,000-$300,000 + Offers Equity

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