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Remote Machine Learning Robotics Jobs in Colorado

Coordinator, Account Management

Westminster, CO · On-site +1

$20 - $26/hr

... remote role. SimioCloud, a Moore company, delivers advanced data, analytics, and machine learning solutions to help nonprofit organizations optimize fundraising and marketing performance. Our ...

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Remote Machine Learning Robotics information

What is a Remote Machine Learning Robotics job?

A Remote Machine Learning Robotics job involves developing and implementing machine learning algorithms to control and improve robotic systems, all while working from a remote location. Professionals in this field use artificial intelligence techniques to enable robots to learn from data and adapt to new tasks. They collaborate with teams virtually, leveraging cloud-based tools and simulation environments to design, test, and deploy robotic solutions. This role typically requires strong programming skills, knowledge of robotics frameworks, and experience with machine learning models.

What is the difference between Remote Machine Learning Robotics vs Remote Data Scientist?

AspectRemote Machine Learning RoboticsRemote Data Scientist
Required CredentialsDegree in Robotics, Computer Science, or related fields; experience with ML algorithms and robotics platformsDegree in Data Science, Statistics, or related fields; proficiency in ML, statistics, and programming
Work EnvironmentHands-on with robotics hardware, simulation environments, and software developmentData analysis, modeling, and visualization primarily on software platforms
Employer & Industry UsageRobotics companies, manufacturing, autonomous vehicles, research labsTech firms, finance, healthcare, research institutions

Remote Machine Learning Robotics focuses on developing intelligent systems that integrate robotics hardware with machine learning algorithms, often requiring hands-on hardware work. In contrast, Remote Data Scientists primarily analyze data and build models using software tools. Both roles involve ML expertise but differ in work environment and industry applications.

How do remote machine learning robotics professionals typically collaborate with hardware teams when working off-site?

Remote machine learning robotics professionals often collaborate closely with hardware teams through regular virtual meetings, shared documentation, and cloud-based development environments. They use simulation tools to test algorithms before deployment and rely on video calls or live streams to observe hardware tests in real time. Effective communication and detailed feedback are essential to ensure that software and hardware integration runs smoothly, despite working from different locations. This collaborative approach helps address issues quickly and keeps projects on track.

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

To thrive as a Remote Machine Learning Robotics Engineer, you need a solid background in robotics, machine learning algorithms, programming (Python, C++), and typically a degree in computer science, robotics, or a related field. Familiarity with robotics frameworks (like ROS), machine learning libraries (such as TensorFlow or PyTorch), and experience with cloud platforms or remote collaboration tools are highly valued. Strong problem-solving abilities, initiative, and effective remote communication skills help you excel in distributed teams. These competencies enable you to develop intelligent robotic systems efficiently, collaborate across locations, and drive innovation in a rapidly evolving field.
What cities in Colorado are hiring for Remote Machine Learning Robotics jobs? Cities in Colorado with the most Remote Machine Learning Robotics job openings:
Distinguished AI/ML Engineer

Distinguished AI/ML Engineer

Frontier Technology Inc.

Colorado Springs, CO • Remote

$190K - $220K/yr

Full-time

Posted 10 days ago


Job description

Overview

FTI Defense delivers mission-focused solutions to the Department of Defense and Intelligence Community through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology.

FTI Defense is seeking a Distinguished AI/ML Engineer to serve as a technical leader, architect, and integrator - designing, building, deploying, and sustaining AI systems that transform complex mission data into trusted, explainable insights.

This is a hands-on builder role, not an analytics management position. The ideal candidate is equally comfortable writing model code, standing up ML pipelines, and integrating AI inference services into operational systems within secure environments. The right candidate blends deep AI/ML engineering expertise with system-level architecture leadership and an ability to unify data engineering, simulation modeling, and responsible AI principles into scalable, mission-ready capabilities.

Responsibilities
  • Architect and integrate hybrid AI systems that combine traditional machine learning, deep learning, large language models (LLMs), and retrieval-augmented generation (RAG) pipelines.
  • Design and deploy scalable AI architectures including APIs, microservices, and model-serving frameworks that integrate seamlessly with analytic, simulation, or operational systems.
  • Lead the full AI/ML lifecycle - from data ingestion and feature engineering through training, deployment, and sustainment within secure DoD environments (IL5/IL6, ATO, GovCloud).
  • Engineer event-driven data pipelines and feature stores for both structured and unstructured data, including text, imagery, and simulation outputs.
  • Ensure Responsible AI practices by embedding traceability, explainability, and confidence scoring into deployed systems.
  • Implement and maintain MLOps pipelines (MLflow, Kubeflow, Airflow, Docker/Kubernetes) to support continuous integration, retraining, and drift detection.
  • Transition R&D prototypes into production, optimizing for mission constraints such as limited compute, edge environments, or disconnected operations.
  • Provide technical leadership and mentorship, setting standards for model quality, architectural design, and ethical AI deployment across programs.
  • Collaborate across engineering, data, and modeling teams to unify FTI's AI portfolio, ensuring interoperability and reuse across mission systems.
  • Support proposal and solution development, providing technical inputs for AI/ML architectures, data strategies, and Responsible AI assurance frameworks.
Education/Qualifications
  • Active Secret clearance required; TS/SCI strongly preferred.
  • Bachelor's degree in Computer Science, Engineering, or a related technical field (Master's or Ph.D. preferred).
  • 10+ years of overall experience in AI/ML development, with 5+ years designing and deploying scalable AI/ML architectures, including at least two full lifecycle implementations (from prototype to operational system).
  • Proficiency in Python, PyTorch, TensorFlow, and modern ML frameworks.
  • Experience designing or deploying systems using vector databases (Milvus, Pinecone, Weaviate), knowledge graphs, and semantic search frameworks.
  • Proven ability to design event-driven data pipelines using Databricks, Spark, Flink, or Kafka.
  • Demonstrated experience deploying AI/ML systems in secure, classified, or edge environments.
  • Familiarity with Responsible AI and assurance principles, including bias detection, explainability, human-machine teaming, and hallucination prevention.
  • Experience integrating AI models into simulation, modeling, or operational planning systems is highly desirable.
  • Experience transitioning R&D systems into accredited production environments.
  • Strong communication and mentoring skills, with the ability to lead technically while remaining deeply hands-on.

For this role, the compensation range for candidates is $190k-$220k . *Note: Starting pay will be based on a number of factors and commensurate with qualifications & experience. FTI has a location-based compensation structure; there may be a different range for candidates in other locations.

#LI-KM1

#LI-Remote

Employment Type: FULL_TIME