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Senior Machine Learning Finance Jobs in Oregon (NOW HIRING)

Cresta

Staff Machine Learning Engineer

OR · On-site +1

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 ...

Netflix

Machine Learning Scientist (L6) - Live Ads

OR · On-site +1

... 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.

Upstart

Principal Software Engineer, Core Pricing

OR · On-site +1

$134K - $180K/yr

We are looking for a seasoned technical leader with a passion for machine learning, finance, experimentation, and distributed systems. If this sounds exciting, we would love to hear from you. How you ...

Nike

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 ...

Instacart

Senior Product Manager, Ads Quality

OR · On-site +1

$126K - $166K/yr

As part of the Ad Product team, you'll sit at the intersection of machine learning, marketplace ... We're looking for a Senior Product Manager to own the systems that drive core auction understanding ...

Deloitte

Senior AI Engineer - SFL Scientific

Portland, OR

$110K - $152K/yr

Work with clients to design, develop, and deploy new architectures to support machine learning ... Work alongside clients every step of the way, helping them navigate new challenges, avoid financial ...

Zillow

OR · On-site

$204K - $326K/yr

About the role As a Principal Machine Learning Engineer on the Agentic Artificial Intelligence team ... S., we help customers navigate buying, selling, financing and renting with greater ease and ...

Upstart

Senior Manager, Privacy Engineering

OR · On-site +1

$100K - $128K/yr

As the Senior Manager, Privacy Engineering at Upstart, you will lead the team responsible for ... Experience building privacy or governance controls for machine learning, AI, financial services ...

Upstart

Principal Credit Analyst

OR · On-site +1

You'll partner closely with Machine Learning, Finance, Product, and Capital teams to translate complex credit dynamics into actionable insights and scalable systems. How you'll make an impact * Own a ...

Upstart

Senior Privacy Engineer

OR · On-site +1

$104K - $143K/yr

Experience working with machine learning systems, financial services, lending, or another regulated data environment * Ability to communicate privacy engineering tradeoffs clearly across technical ...

SOSi

Senior Data Scientist

OR · On-site +1

SOSi is seeking a Senior Data Scientist to support mission requirements for a structured approach ... Master's degree in Data Science, Machine Learning, Statistics, or a related field, or; * nine (9) ...

SOSi

Senior Data Scientist

OR · On-site

SOSi is seeking a Senior Data Scientist to support mission requirements for a structured approach ... Master's degree in Data Science, Machine Learning, Statistics, or a related field, or; * nine (9) ...

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All JobsMachine Learning Finance JobsSenior Machine Learning Finance JobsSenior Machine Learning Finance Jobs in Oregon

Senior Machine Learning Finance information

What is the difference between Senior Machine Learning Finance vs Quantitative Analyst?

AspectSenior Machine Learning FinanceQuantitative Analyst
Required CredentialsAdvanced degrees in CS, Data Science, or Finance; experience with ML frameworksDegrees in Finance, Economics, or Mathematics; strong statistical background
Work EnvironmentTech-driven finance teams, focus on ML model developmentTrading floors, investment firms, focus on quantitative modeling
Industry UsageFinancial institutions leveraging AI/ML for trading, risk, and asset managementAsset management, hedge funds, investment banks

While both roles involve quantitative skills, Senior Machine Learning Finance focuses on developing and deploying machine learning models within finance, whereas Quantitative Analysts primarily build statistical models for trading and risk assessment. The former emphasizes AI/ML expertise, while the latter centers on traditional quantitative methods.

What cities in Oregon are hiring for Senior Machine Learning Finance jobs?

Cities in Oregon with the most Senior Machine Learning Finance job openings:

Senior Machine Learning Finance jobs near you

Staff Machine Learning Engineer

Cresta

OR • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 5 days ago

Key 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.

  • Own evaluation strategy for complex, non-deterministic AI systems, including offline benchmarking, online experimentation, LLM-as-a-judge methodologies, and systematic failure analysis.

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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