Machine Learning Visa Sponsorship Jobs in Colorado
Colorado's machine learning job market centers on Denver and Boulder, where companies like Google, Lockheed Martin, and a dense cluster of healthtech and aerospace firms actively hire ML engineers and data scientists. The state's proximity to top research universities, including CU Boulder and Colorado State, creates a steady pipeline of technical talent and employers experienced with visa sponsorship.
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Get Access To All JobsINTRODUCTION
Are you passionate about shaping the future of humanity's presence in space? Lunar Outpost, a trailblazer in space robotics, invites you to join our team! Lunar Outpost is dedicated to creating a sustainable presence in space, while also driving positive impacts here on Earth. We are seeking a talented Senior Autonomy Machine Learning Engineer.
ROLE AND RESPONSIBILITIES
As a Senior Autonomy Machine Learning Engineer, you will research, develop, train, evaluate, and deploy machine learning models for Lunar Outpost’s lunar rovers, command-and-control platforms, terrestrial robotic systems, and orbital assets. Working at the intersection of robotics, autonomy, AI, and space exploration, you will develop technologies that enable robotic systems to perceive their environment, interpret operator intent, reason about mission objectives, generate plans, and safely execute complex tasks with reduced operator oversight. Your work will include transformer-based architectures, vision-language models, multimodal foundation models, robot learning, and intelligent planning and decision-support systems. You will help build datasets, evaluation frameworks, software infrastructure, and deployment pipelines that support applications ranging from natural-language vehicle control to onboard reasoning, anomaly detection, mission summarization, and multi-robot supervision. You will collaborate closely with robotics, software, simulation, and command-and-control engineering teams to transition emerging AI research into reliable capabilities.
Take the #NextLeap with Lunar Outpost and work on the Pegasus LTV, which will carry NASA astronauts farther than they've ever been before on the lunar surface!
Key Responsibilities:
- Research, design, train, fine-tune, and evaluate transformer-based machine learning architectures for autonomous robotic and command-and-control applications
- Develop vision-language-action models, vision-language models, and other multimodal models that connect operator intent and sensor observations to robot plans and actions
- Build capabilities for natural-language command interpretation, task decomposition, mission planning, action generation, operator decision support, and autonomous task execution
- Develop human-robot teaming capabilities that enable operators to efficiently supervise and command multiple robotic assets
- Create systems for mission summarization, anomaly detection, situational awareness, course-of-action generation, and operator-reviewable recommendations
- Integrate machine learning models with robotic platforms, simulation environments, command-and-control software, and autonomy frameworks
- Conduct hardware-in-the-loop tests, field tests, and structured demonstrations to validate capabilities under realistic operating conditions
- Participate in design reviews, trade studies, technical risk assessments, test-readiness reviews, and demonstrations
BASIC QUALIFICATIONS
- Bachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, Robotics, Electrical Engineering, Computer Engineering, Aerospace Engineering, or a related technical field, or equivalent practical experience
- 3 to 5 years of relevant professional, academic, or research experience developing machine learning systems, autonomous systems, or intelligent robotic applications
- Experience developing and evaluating deep learning models using Python and a modern machine learning framework such as PyTorch, JAX, or TensorFlow
- Experience in at least one of the following areas:
- Vision-language models or multimodal foundation models
- Robot learning, imitation learning, or reinforcement learning
- Natural-language planning, tool use, or agentic systems
- Autonomous planning, reasoning, or task execution
- Experience preparing datasets, implementing training pipelines, defining evaluation metrics, and analyzing model performance
- Strong software engineering skills, including experience writing maintainable and testable software
- Experience with Linux-based development environments, Git, and collaborative software development workflows
- Ability to translate research concepts into working prototypes and evaluate those prototypes against measurable system objectives
- Ability to communicate complex technical concepts, experimental results, limitations, and risks to multidisciplinary teams
- Comfortable working in a research-oriented, agile, and interdisciplinary environment where requirements and technical approaches may evolve rapidly
- U.S. Person
PREFERRED QUALIFICATIONS
- Master’s degree or Ph.D. in Machine Learning, Artificial Intelligence, Robotics, Computer Science, or a related field
- Experience developing or fine-tuning VLMs, VLAs, large language models, or multimodal transformer architectures
- Experience with robot foundation models, action tokenization, multimodal policy learning, hierarchical policies, or language-conditioned control
- Experience applying supervised fine-tuning, parameter-efficient fine-tuning, preference optimization, imitation learning, or reinforcement learning to foundation models
- Experience with robotics middleware and autonomy frameworks such as ROS2
- Experience integrating learned models with robot perception, planning, control, or command-and-control systems
- A record of technical innovation demonstrated through deployed systems, open-source contributions, publications, patents, or significant project achievements
COMPENSATION & BENEFITS
Compensation level and base salary are competitively structured and thoughtfully determined based on factors such as relevant skills, experience, education, and the scope of the role.
- Comprehensive health coverage: Medical, dental, and vision benefits, with 70% of premiums covered by the employer
- Paid time off: Three (3) weeks per year of vacation
- Retirement plan: Up to 4% employer match on 401(k) contributions
- Paid holidays: 11 company-recognized holidays
- Parental leave
- Educational reimbursement opportunities to support company objectives, continued learning, and career development
Lunar Outpost Inc. is an equal opportunity employer. Lunar Outpost Inc. does not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, and gender identity), national origin, ethnicity, age, disability, veteran status, genetic information, or any other characteristic protected by applicable law. All employees, including executives and human resources personnel, are expected to conduct themselves with professionalism and treat others with dignity and respect in accordance with this policy.
INTRODUCTION
Are you passionate about shaping the future of humanity's presence in space? Lunar Outpost, a trailblazer in space robotics, invites you to join our team! Lunar Outpost is dedicated to creating a sustainable presence in space, while also driving positive impacts here on Earth. We are seeking a talented Senior Autonomy Machine Learning Engineer.
ROLE AND RESPONSIBILITIES
As a Senior Autonomy Machine Learning Engineer, you will research, develop, train, evaluate, and deploy machine learning models for Lunar Outpost’s lunar rovers, command-and-control platforms, terrestrial robotic systems, and orbital assets. Working at the intersection of robotics, autonomy, AI, and space exploration, you will develop technologies that enable robotic systems to perceive their environment, interpret operator intent, reason about mission objectives, generate plans, and safely execute complex tasks with reduced operator oversight. Your work will include transformer-based architectures, vision-language models, multimodal foundation models, robot learning, and intelligent planning and decision-support systems. You will help build datasets, evaluation frameworks, software infrastructure, and deployment pipelines that support applications ranging from natural-language vehicle control to onboard reasoning, anomaly detection, mission summarization, and multi-robot supervision. You will collaborate closely with robotics, software, simulation, and command-and-control engineering teams to transition emerging AI research into reliable capabilities.
Take the #NextLeap with Lunar Outpost and work on the Pegasus LTV, which will carry NASA astronauts farther than they've ever been before on the lunar surface!
Key Responsibilities:
- Research, design, train, fine-tune, and evaluate transformer-based machine learning architectures for autonomous robotic and command-and-control applications
- Develop vision-language-action models, vision-language models, and other multimodal models that connect operator intent and sensor observations to robot plans and actions
- Build capabilities for natural-language command interpretation, task decomposition, mission planning, action generation, operator decision support, and autonomous task execution
- Develop human-robot teaming capabilities that enable operators to efficiently supervise and command multiple robotic assets
- Create systems for mission summarization, anomaly detection, situational awareness, course-of-action generation, and operator-reviewable recommendations
- Integrate machine learning models with robotic platforms, simulation environments, command-and-control software, and autonomy frameworks
- Conduct hardware-in-the-loop tests, field tests, and structured demonstrations to validate capabilities under realistic operating conditions
- Participate in design reviews, trade studies, technical risk assessments, test-readiness reviews, and demonstrations
BASIC QUALIFICATIONS
- Bachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, Robotics, Electrical Engineering, Computer Engineering, Aerospace Engineering, or a related technical field, or equivalent practical experience
- 3 to 5 years of relevant professional, academic, or research experience developing machine learning systems, autonomous systems, or intelligent robotic applications
- Experience developing and evaluating deep learning models using Python and a modern machine learning framework such as PyTorch, JAX, or TensorFlow
- Experience in at least one of the following areas:
- Vision-language models or multimodal foundation models
- Robot learning, imitation learning, or reinforcement learning
- Natural-language planning, tool use, or agentic systems
- Autonomous planning, reasoning, or task execution
- Experience preparing datasets, implementing training pipelines, defining evaluation metrics, and analyzing model performance
- Strong software engineering skills, including experience writing maintainable and testable software
- Experience with Linux-based development environments, Git, and collaborative software development workflows
- Ability to translate research concepts into working prototypes and evaluate those prototypes against measurable system objectives
- Ability to communicate complex technical concepts, experimental results, limitations, and risks to multidisciplinary teams
- Comfortable working in a research-oriented, agile, and interdisciplinary environment where requirements and technical approaches may evolve rapidly
- U.S. Person
PREFERRED QUALIFICATIONS
- Master’s degree or Ph.D. in Machine Learning, Artificial Intelligence, Robotics, Computer Science, or a related field
- Experience developing or fine-tuning VLMs, VLAs, large language models, or multimodal transformer architectures
- Experience with robot foundation models, action tokenization, multimodal policy learning, hierarchical policies, or language-conditioned control
- Experience applying supervised fine-tuning, parameter-efficient fine-tuning, preference optimization, imitation learning, or reinforcement learning to foundation models
- Experience with robotics middleware and autonomy frameworks such as ROS2
- Experience integrating learned models with robot perception, planning, control, or command-and-control systems
- A record of technical innovation demonstrated through deployed systems, open-source contributions, publications, patents, or significant project achievements
COMPENSATION & BENEFITS
Compensation level and base salary are competitively structured and thoughtfully determined based on factors such as relevant skills, experience, education, and the scope of the role.
- Comprehensive health coverage: Medical, dental, and vision benefits, with 70% of premiums covered by the employer
- Paid time off: Three (3) weeks per year of vacation
- Retirement plan: Up to 4% employer match on 401(k) contributions
- Paid holidays: 11 company-recognized holidays
- Parental leave
- Educational reimbursement opportunities to support company objectives, continued learning, and career development
Lunar Outpost Inc. is an equal opportunity employer. Lunar Outpost Inc. does not discriminate on the basis of race, color, religion, sex (including pregnancy, sexual orientation, and gender identity), national origin, ethnicity, age, disability, veteran status, genetic information, or any other characteristic protected by applicable law. All employees, including executives and human resources personnel, are expected to conduct themselves with professionalism and treat others with dignity and respect in accordance with this policy.
Machine Learning Job Roles in Colorado
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Search Machine Learning Jobs in ColoradoMachine Learning Jobs in Colorado: Frequently Asked Questions
Which companies sponsor visas for machine learning roles in Colorado?
Several large employers in Colorado have consistent H-1B visa sponsorship histories for machine learning roles. Google's Boulder engineering office, Lockheed Martin, Palantir (which has significant Denver presence), and healthtech companies like DaVita and Optum are among those that have filed LCAs for ML and AI positions. Aerospace and defense contractors along the Front Range also recruit ML engineers and have established immigration processes.
Which visa types are most common for machine learning roles in Colorado?
The H-1B is the most common visa for machine learning engineers and data scientists in Colorado, as ML roles typically satisfy the specialty occupation requirement given the degree-level technical skills involved. Australians may pursue the E-3 visa as an alternative with no lottery. Candidates with exceptional research records or published work may also qualify for the O-1A. TN visa status is available to Canadian and Mexican nationals in qualifying computer-related occupations.
Which cities in Colorado have the most machine learning sponsorship jobs?
Denver and Boulder account for the majority of machine learning visa sponsorship activity in Colorado. Boulder's tech corridor hosts a concentration of AI startups and research-driven companies, partly due to CU Boulder's strong computer science programs. Denver attracts larger enterprise employers across healthtech, fintech, and aerospace. Colorado Springs has a smaller but active market tied to defense and government contracting, where ML roles in computer vision and data analysis appear regularly.
How to find machine learning visa sponsorship jobs in Colorado?
Migrate Mate is built specifically for international job seekers and filters machine learning roles in Colorado by visa sponsorship eligibility, saving you from manually screening hundreds of listings. You can browse current openings from employers who have demonstrated sponsorship history for ML and AI positions across Denver, Boulder, and the broader Front Range. Filtering by state and role on Migrate Mate surfaces opportunities that match both your technical background and immigration needs.
Are there state-specific factors that affect machine learning visa sponsorship in Colorado?
Colorado's Equal Pay for Equal Work Act requires employers to include compensation ranges in job postings, which gives machine learning candidates useful context when evaluating whether a role meets prevailing wage requirements under H-1B rules. The state's strong university pipeline from CU Boulder and Colorado School of Mines means employers here are generally familiar with OPT and STEM OPT extensions, making the transition from student status to sponsored employment more straightforward at many local companies.
What is the prevailing wage for sponsored machine learning jobs in Colorado?
U.S. employers sponsoring a visa must pay at least the prevailing wage, which is what workers in the same role, area, and experience level typically earn. The Department of Labor sets this rate to make sure companies aren't hiring foreign workers simply because they'd accept lower pay than a U.S. worker. It varies by job title, location, and experience. You can look up current prevailing wage rates for any occupation and location using the OFLC Wage Search page.