ZipRecruiter

Log In

2

Remote Reinforcement Learning Jobs in Colorado (NOW HIRING)

Sovrn

Senior AI/ML Data Scientist

Boulder, CO · On-site +1

Deep technical proficiency across classical ML (supervised/unsupervised), reinforcement learning ... For exceptional candidates we would consider remote locations. Applicants need to be able to ...

People also search for

All JobsRemote Reinforcement Learning JobsRemote Reinforcement Learning Jobs in Colorado

Remote Reinforcement Learning information

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

To thrive as a Remote Reinforcement Learning Engineer, you need a strong background in machine learning, statistics, and programming (especially Python), often supported by an advanced degree in computer science or a related field. Familiarity with frameworks such as TensorFlow, PyTorch, and RL-specific libraries like OpenAI Gym, along with experience using cloud computing platforms, is typically required. Excellent problem-solving skills, self-motivation, and effective remote communication help individuals excel in distributed teams. These skills ensure the successful design, implementation, and deployment of reinforcement learning solutions while collaborating efficiently in a remote work environment.

What are common challenges faced when working remotely in a Reinforcement Learning role and how can they be addressed?

Working remotely in a Reinforcement Learning role often involves overcoming communication barriers with cross-functional teams, managing large-scale experiments without on-site resources, and staying updated with rapidly evolving research. To address these challenges, it's important to establish regular check-ins with colleagues, utilize cloud-based platforms for experiment management, and participate in virtual seminars or journal clubs. Developing strong self-motivation and time management skills is also crucial to maintain productivity in a remote environment.

What is a Remote Reinforcement Learning job?

A Remote Reinforcement Learning job involves developing and applying reinforcement learning algorithms while working from a location outside of a traditional office environment. Professionals in this field focus on creating systems where agents learn optimal behaviors through trial and error, often using feedback from their environment. These jobs typically require expertise in machine learning, programming, and mathematics, and are commonly found in industries like robotics, gaming, and autonomous systems. Working remotely allows researchers and engineers to collaborate with global teams using digital tools and platforms.

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

AspectRemote Reinforcement Learning
Required CredentialsMaster's or PhD in Computer Science, AI, or related fields; knowledge of RL algorithms
Work EnvironmentResearch-focused, experimental, often involves simulation and algorithm development
Employer & Industry UsageTech companies, research labs, AI startups focusing on autonomous systems
Common Search & Comparison IntentUnderstanding specialized AI roles, research focus, and technical skills

Remote Reinforcement Learning specialists focus on developing algorithms that enable machines to learn through trial and error in simulated or real environments. In contrast, Remote Machine Learning Engineers typically work on deploying and optimizing various machine learning models across applications. While both roles require strong programming skills and knowledge of AI, reinforcement learning emphasizes decision-making processes, whereas machine learning engineering covers a broader range of models and deployment strategies.

What are popular job titles related to Remote Reinforcement Learning jobs in Colorado? For Remote Reinforcement Learning jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Remote Reinforcement Learning jobs in Colorado look for? The top searched job categories for Remote Reinforcement Learning jobs in Colorado are:
Remote Reinforcement Learning jobs near you
Infographic showing various Remote Reinforcement Learning job openings in Colorado as of May 2026, with employment types broken down into 81% Full Time, 15% Part Time, and 4% Contract. Highlights an 57% Physical, 8% Hybrid, and 35% Remote job distribution.
Senior AI Engineer, Agentic Evaluation & V&V

Senior AI Engineer, Agentic Evaluation & V&V

Slingshot Aerospace

Colorado Springs, CO • On-site, Remote

$150K - $250K/yr

Other

Posted 28 days ago

Job description

Meet Slingshot

At Slingshot Aerospace,we'reon a mission to make space safer and more secure for everyone. Our work directlyimpactsglobal security, disaster response, climate monitoring, and the critical infrastructure that connects our world.We'rea team of builders, thinkers, and problem-solvers who believe that the next generation of space operations will be powered by better data and smarter software.

WhatYou'llBe Launching

As a Senior AI Engineer focused on Agentic Evaluation and Verification and Validation (V&V), you will join the AI and Data Science team within Slingshot's Research and Development organization. You will contribute to advancing how intelligent systems are evaluated andvalidatedfor mission-critical space operations.

This role focuses on building and scaling evaluation frameworks, benchmarks, and simulation-backed validation systems for agentic AI systems, including multi-step, tool-using, and autonomous decision-making workflows powered by LLMs and reinforcement learning. Your work will directly support the development of reliable and trustworthy autonomous mission planning systems.

You will partner closely with AI researchers and domain experts to translate real-world mission concepts into structured, testable evaluation systems.

Your Mission (Should you choose to accept it)

  • Extend andmaintainSlingshot's V&V SDK and evaluation framework for simulation-backed validation of agentic AI systems
  • Design and implement agent-level and end-to-end evaluations, including benchmark scenarios, scoring logic, and experiment harnesses
  • Build benchmark scenarios and tooling that measure planning, reasoning, and operational performance for autonomous mission planning systems
  • Translate astrodynamics and mission-domain concepts into executable evaluation scenarios and simulation configurations
  • Develop reusable SDK interfaces, adapters, and evaluation utilities that connect V&V systems, TALOS benchmarks, and agent workflows
  • Define and apply metrics for capability evaluation, failure analysis, regression detection, and comparative benchmarking
  • Partner with cross-functional teams toidentifyevaluation needs and contribute to improving coverage of critical capabilities
  • Contribute to best practices for evaluating complex, autonomous AI systems
  • Uphold strong engineering standards through testing, documentation, reproducibility, and maintainable system design

Pre-flight Checklist

  • 6+ years of experience in software engineering, machine learning engineering, applied AI, or equivalent experience
  • Strong Python engineering skills with experience building SDKs, libraries, or evaluation tooling
  • Experience designing evaluation frameworks, benchmarks, metrics, or test harnesses for AI/ML systems
  • Ability to analyze system behavior,identifyfailure modes, and evaluate performance in complex autonomous or semi-autonomous systems
  • Familiarity with modern agent frameworks, orchestration patterns, or protocol-based integrations
  • Experience working in cross-functional, multidisciplinary teams
  • Strong written and verbal communication skills
  • Bachelor's degree in a relevant science or engineering field, or equivalent experience
  • Must be a U.S. citizen and eligible to obtain andmaintaina government security clearance

Bonus Cargo

  • Experience in autonomous systems such as self-driving or ADAS, includingperception, planning, simulation, or safety validation
  • Experience developing or evaluating agentic AI systems, including multi-step, tool-using, or autonomous workflows (e.g., LLM-based agents, planning agents, or reinforcement learning approaches)
  • Experience with reinforcement learning systems and simulation-based evaluation
  • Familiarity with benchmark design, experiment tracking, and trace-based evaluation workflows
  • Experience with orchestration frameworks such asLangGraphor similar tools
  • Knowledge of astrodynamics, orbital mechanics, or spacecraft mission planning
  • Experience translating mission or operational concepts into measurable evaluation scenarios
  • Familiarity with physics-based simulation, trajectory analysis, or space-domain modeling
  • Experience with observability and experiment tooling such asMLflow, Opik, or similar platforms
  • Experience transitioning advanced research systems into production environments

We'rebuilding a constellation here, not looking for identical satellites. Every member of the team brings different capabilities to the same mission. If your orbit intersects with ours andyou'remission-ready, send it.

Location: Remote, US

Salary:$150,000-$250,000

Classification:Full time Exempt (learned professional exemption)

US-based Candidates: we are currently only able to hire residents of the following U.S. states: AL, AZ, CA, CO, DC, FL, GA, HI, IL, IN, KS, MA, MD, MI, MN, MO, MT, NC, NJ, NM, NV, NY, OH, OK, OR, RI, TN, TX, UT, VA, WA, WI, WV We are unable to consider candidates residing in other U.S. states at this time.

Internationally-based Candidates: we are currently only able to hire residents of the following locations: United Kingdom. We are unable to consider candidates residing in other countries at this time.

Equity, Diversity & Inclusion are key to our success. We are an Equal Opportunity Employer and our employees are people with different strengths, experiences, and backgrounds, who share a passion for creating a safer, more connected world. Diversity not only includes race and gender identity, but also national origin, citizenship, sex, color, veteran status, disability, genetic information, or any other protected characteristic that is part of one's identity. All of our employees' points of view are key to our success, and we embrace individuality.

Apply