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Reinforcement Learning Engineer Jobs in Oregon (NOW HIRING)

Black Duck Software, Inc.

Director Sales Enablement

OR · On-site +1

Partnering closely with Sales Leadership, Product Marketing, Sales Engineering, Revenue Operations ... adult learning principles, practical application, repetition, coaching, and reinforcement.

New

Nvidia

Senior Solutions Architect, Agentic AI

OR · On-site +1

We want a creative, diligent, and curious engineer energized by agentic AI and ready to make ... Applies test-time compute, reinforcement learning, inference optimization, and post-training.

SOLV Energy

Senior SCADA Engineer, Design (Remote)

OR · On-site +1

$104K - $143K/yr

Mentor junior and mid-level engineers through technical review, knowledge sharing, and reinforcement of design standardswhilefosteringa culture of continuous learning and engineering excellence.

Lam Research

Business Systems Analyst 5

Tualatin, OR · On-site

Mentor and coach quality engineers and analysts across the factory network to leverage the ... learning) Intermediate skills in a scripting language such as python / R Proven ability to solve ...

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All JobsReinforcement Learning Engineer JobsReinforcement Learning Engineer Jobs in Oregon

Reinforcement Learning Engineer information

See Oregon salary details

$40.2K

$122.5K

$202.5K

How much do reinforcement learning engineer jobs pay per year?

As of Sep 13, 2026, the average yearly pay for reinforcement learning engineer in Oregon is $122,502.00, according to ZipRecruiter salary data. Most workers in this role earn between $87,800.00 and $160,200.00 per year, depending on experience, location, and employer.

What is a reinforcement learning engineer?

Reinforcement Learning Engineers are specialized professionals who design, develop, and implement algorithms based on reinforcement learning, a type of machine learning where agents learn to make decisions by receiving rewards or penalties. They work on building models that enable machines to learn optimal actions through trial and error in complex environments. Their responsibilities often include developing RL architectures, tuning hyperparameters, running simulations, and applying RL methods to real-world problems like robotics, gaming, or recommendation systems. RL Engineers typically have strong backgrounds in computer science, mathematics, and deep learning, along with experience in programming languages like Python and frameworks such as TensorFlow or PyTorch.

What are some common challenges faced by reinforcement learning engineers when deploying models in real-world environments?

One of the main challenges Reinforcement Learning (RL) Engineers face is bridging the gap between simulation and real-world deployment. Models that perform well in controlled environments may struggle with unpredictable data, safety constraints, or limited feedback in production. Additionally, RL algorithms often require significant computational resources and careful tuning to avoid instability. Collaboration with domain experts and software engineers is essential to address these issues and ensure successful integration of RL solutions into existing systems.

What are the key skills and qualifications needed to thrive as a reinforcement learning engineer, and why are they important?

To thrive as a Reinforcement Learning Engineer, you need a strong background in machine learning, mathematics (especially probability and statistics), and programming languages like Python, often supported by a relevant degree in computer science or engineering. Familiarity with deep learning frameworks (such as TensorFlow or PyTorch), RL libraries (like OpenAI Gym), and cloud computing platforms is typically required. Problem-solving skills, creativity, and effective collaboration help set outstanding engineers apart in this field. These competencies enable the design and deployment of advanced RL solutions that address real-world challenges and drive innovation.

What is the difference between Reinforcement Learning Engineer vs Machine Learning Engineer?

AspectReinforcement Learning EngineerMachine Learning Engineer
CredentialsBachelor's/Master's in CS, AI, or related; experience with RL frameworksBachelor's/Master's in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on RL applicationsTech companies, data-driven firms, AI departments across industries
Industry UsageSpecialized in RL projects like robotics, game AI, autonomous systemsBroader applications including predictive modeling, NLP, computer vision

Reinforcement Learning Engineers focus on developing algorithms that learn through interactions with environments, often in robotics or gaming. Machine Learning Engineers work on a wider range of models and applications. While both roles require strong programming and math skills, RL Engineers specialize in sequential decision-making, whereas ML Engineers handle diverse data-driven tasks across industries.

What are popular job titles related to Reinforcement Learning Engineer jobs in Oregon?

For Reinforcement Learning Engineer jobs in Oregon, the most frequently searched job titles are:

What job categories do people searching Reinforcement Learning Engineer jobs in Oregon look for?

The top searched job categories for Reinforcement Learning Engineer jobs in Oregon are:

What cities in Oregon are hiring for Reinforcement Learning Engineer jobs?

Cities in Oregon with the most Reinforcement Learning Engineer job openings:

Reinforcement Learning Engineer jobs near you
Infographic showing various Reinforcement Learning Engineer job openings in Oregon as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 83% Physical, 3% Hybrid, and 14% Remote job distribution, with an average salary of $122,502 per year, or $58.9 per hour.

Director Sales Enablement

OR • On-site, Remote

Black Duck Software, Inc.
Software Development • 5 - 10K employees
Learn more about Black Duck Software, Inc.external

Full-time

Posted 3 days ago

New

Job description

Director, Sales Enablement

Position Summary

Black Duck is seeking an experienced and dynamic Director of Sales Enablement to lead the development and execution of a world-class sales training and readiness strategy. This leader will ensure customer-facing commercial teams possess the knowledge, skills, tools, and behaviors required to consistently achieve revenue goals and deliver exceptional customer experiences.

The Director will build and scale comprehensive onboarding, continuous learning, sales coaching, certification, and leadership development programs across the global sales organization. Partnering closely with Sales Leadership, Product Marketing, Sales Engineering, Revenue Operations, and Customer Success, this individual will drive excellence in sales execution, increase seller productivity, and accelerate revenue growth.

The ideal candidate combines expertise in adult learning, enterprise sales methodologies, coaching, and change management with a proven record of improving seller performance in a high-growth enterprise software environment.

Key ResponsibilitiesGlobal Sales Training Strategy
  • Develop and execute the global sales enablement and training strategy aligned with revenue objectives, go-to-market priorities, and field performance needs.
  • Create a scalable learning framework that supports onboarding, ongoing seller development, leadership readiness, and continuous skill advancement.
  • Establish consistent training and readiness standards across Sales, Sales Development, Renewals, Channel, and Sales Engineering.
  • Advise sales leaders on talent development, performance improvement, and sales effectiveness priorities.
New Hire Onboarding & Ramp-to-Productivity
  • Design and manage a best-in-class onboarding experience that accelerates new-hire readiness and time-to-productivity.
  • Build structured 30/60/90-day onboarding plans, role-based learning paths, certifications, practice activities, and manager coaching guides.
  • Develop tailored onboarding programs for Account Executives, Account Managers, Sales Development Representatives, Sales Engineers, Renewals professionals, Channel teams, and Sales Leaders.
  • Assess onboarding effectiveness through learner feedback, manager observations, readiness measures, and business outcomes, then continuously improve the program.
Sales Skills Development

Build and deliver practical, role-based training that improves seller performance in the following areas:

  • Value-based and consultative selling
  • Discovery, qualification, and customer needs analysis
  • Executive conversations and business storytelling
  • Account and territory planning
  • Pipeline generation and opportunity progression
  • Competitive positioning and objection handling
  • Negotiation and closing
  • Forecasting discipline
  • Renewal, expansion, and cross-sell motions

Create progressive development paths for sellers at different experience levels and deliver learning through instructor-led sessions, virtual programs, workshops, peer practice, self-paced modules, and field reinforcement.

Sales Methodology & Process Adoption
  • Lead the deployment, training, adoption, and reinforcement of the company's sales methodology and qualification framework.
  • Translate sales processes into clear, teachable behaviors that sellers and managers can apply during live opportunities.
  • Partner with Sales Leadership and Revenue Operations to embed methodology, process discipline, and best practices into daily sales workflows.
  • Create practice scenarios, deal clinics, reinforcement activities, and coaching tools that improve opportunity management and execution consistency.
Manager Enablement & Coaching Excellence
  • Build a consistent coaching culture across the global sales organization.
  • Develop frontline sales managers into effective coaches who can diagnose performance gaps, reinforce skills, and improve seller execution.
  • Create manager toolkits, coaching frameworks, observation guides, scorecards, and team-based reinforcement plans.
  • Facilitate manager training on coaching conversations, pipeline inspection, opportunity reviews, performance feedback, and team development.
Product, Market & Competitive Readiness
  • Ensure field teams remain current on Black Duck solutions, target customer challenges, industry trends, buyer priorities, and the competitive landscape.
  • Partner with Product Marketing, Product Management, and Sales Engineering to deliver launch training and ongoing solution readiness.
  • Create knowledge assessments and certifications that validate product, solution, messaging, and competitive proficiency.
  • Help sellers translate technical capabilities into differentiated customer value and measurable business outcomes.
Learning Experience & Facilitation
  • Design engaging learning experiences using adult learning principles, practical application, repetition, coaching, and reinforcement.
  • Facilitate high-impact training for global audiences, including new-hire cohorts, sales teams, managers, and sales leadership.
  • Build a network of subject matter experts and field facilitators to expand training reach and ensure real-world relevance.
  • Maintain a global training calendar coordinated with sales priorities, product launches, and major commercial initiatives.
Enablement Analytics & Performance Improvement

Define and monitor measures that demonstrate training effectiveness and field impact, including:

  • New-hire ramp and time-to-productivity
  • Training participation, completion, and learner satisfaction
  • Knowledge and skill certification results
  • Manager coaching activity and effectiveness
  • Sales methodology adoption
  • Seller productivity, pipeline progression, win rates, and quota attainment

Use performance data, field feedback, and manager input to identify skill gaps, prioritize interventions, and provide readiness recommendations to sales leadership.

Leadership & Program Management
  • Build, lead, coach, and develop a high-performing Sales Enablement team.
  • Manage training budgets, external partners, learning platforms, program resources, and vendor relationships.
  • Create clear operating rhythms, stakeholder governance, and accountability for training delivery and reinforcement.
  • Foster a culture of continuous learning, collaboration, practical application, accountability, and measurable results.
QualificationsRequired Qualifications
  • Bachelor's degree or equivalent practical experience.
  • 10+ years of experience in Sales Enablement, Sales Training, Learning & Development, Commercial Excellence, or a related function.
  • 5+ years of leadership experience managing enablement, training, or learning teams.
  • Experience building and scaling sales onboarding, continuous learning, certification, and manager coaching programs within an enterprise software or SaaS organization.
  • Strong expertise in instructional design, adult learning, facilitation, coaching, and performance consulting.
  • Demonstrated ability to translate business priorities and performance gaps into effective learning solutions.
  • Excellent executive communication, presentation, facilitation, influence, and stakeholder management skills.
  • Analytical orientation with experience using readiness and performance measures to improve programs and business outcomes.
Preferred Qualifications
  • Experience in cybersecurity, application security, DevSecOps, or enterprise software.
  • Experience implementing and reinforcing structured sales methodologies such as MEDDPICC, Challenger, Command of the Message, Force Management, or Value Selling.
  • Experience supporting geographically distributed, global sales teams.
  • Familiarity with learning management systems, sales enablement platforms, CRM technology, virtual facilitation tools, and content delivery platforms.

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