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Remote Machine Learning Postdoc Jobs in Colorado

Auria

Chief Engineer

Colorado Springs, CO · On-site +1

$160K - $190K/yr

This role is remote but with a location preference of Colorado Springs, CO. Support of a broad ... machine learning (ML); and Cybersecurity and zero-trust architecture. WHAT YOU CAN EXPECT TO DO:

Moore

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 ...

Auria

Chief Engineer

Colorado Springs, CO · On-site +1

$169K - $190K/yr

This role is remote but with a location preference of Colorado Springs, CO. Support of a broad ... machine learning (ML); and Cybersecurity and zero-trust architecture. WHAT YOU CAN EXPECT TO DO:

Auria

Technical Program Manager

Colorado Springs, CO · On-site +1

$145K - $180K/yr

This role is remote but with a location preference of Colorado Springs, CO. Support of a broad ... machine learning (ML); and Cybersecurity and zero-trust architecture. WHAT YOU CAN EXPECT TO DO:

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Remote Machine Learning Postdoc information

Is ML a high paying job?

Machine learning postdoctoral positions are generally well-paid compared to many academic roles, with salaries often ranging from $60,000 to over $100,000 annually depending on experience, location, and funding. These roles typically require strong programming skills in Python or R and knowledge of algorithms and data analysis, which can contribute to higher compensation levels.

Is a PhD in ML worth it?

A PhD in machine learning can enhance qualifications for a remote machine learning postdoc position, often leading to higher-level research opportunities and increased earning potential. However, it requires significant time investment and may not be necessary for industry roles that value practical skills and experience with tools like Python and TensorFlow. The decision depends on career goals and the specific requirements of the desired position.

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

A Remote Machine Learning Postdoc requires a PhD in computer science, statistics, or a related field, with expertise in machine learning algorithms, statistical modeling, and research methodologies. Proficiency in programming languages like Python or R, experience with machine learning frameworks such as TensorFlow or PyTorch, and familiarity with version control systems (e.g., Git) are typically necessary. Strong written and verbal communication, self-motivation, and collaboration skills are vital for remote research and effective teamwork. These capabilities enable impactful independent research, smooth collaboration across distributed teams, and the successful dissemination of findings to the wider scientific community.

Is a postdoc harder than a PhD?

A remote machine learning postdoc typically involves more specialized research, higher expectations for independence, and often requires advanced skills in programming and data analysis. While a PhD focuses on completing a dissertation and gaining foundational expertise, a postdoc emphasizes producing publishable research and may involve longer hours and greater responsibility, making it generally more demanding in terms of research output and expertise. However, the difficulty varies based on individual experience and research environment.

What is a Remote Machine Learning Postdoc?

A Remote Machine Learning Postdoc is a postdoctoral researcher specializing in machine learning who works predominantly or entirely from a location outside their host institution, often from home. Their work involves conducting advanced research, developing new algorithms, analyzing data, and publishing findings related to machine learning while collaborating virtually with faculty and research teams. This role is ideal for researchers seeking flexibility or those who cannot relocate but wish to contribute to academic or industrial research from a distance.

Do you need H-1B for postdoc?

A remote machine learning postdoctoral position typically does not require H-1B sponsorship if the candidate is already authorized to work in the country, such as through a visa or citizenship. However, international candidates may need H-1B or other work visas depending on the employer and local immigration laws. Employers often sponsor visas for postdocs to comply with legal requirements and facilitate employment.

What are some common challenges faced by remote machine learning postdocs when collaborating with research teams?

Remote machine learning postdocs often encounter challenges related to communication and coordination, especially when working across different time zones or with teams that have varying schedules. Effective collaboration usually requires proactive communication through virtual meetings, shared code repositories, and regular progress updates. Building rapport with colleagues and staying engaged with ongoing research discussions can take extra effort remotely, but leveraging collaborative tools and participating in virtual seminars or group chats can help bridge the gap. Being organized and self-motivated is key to ensuring productive contributions to the team’s research objectives.
What are popular job titles related to Remote Machine Learning Postdoc jobs in Colorado? For Remote Machine Learning Postdoc jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning Postdoc jobs in Colorado look for? The top searched job categories for Remote Machine Learning Postdoc jobs in Colorado are:
What cities in Colorado are hiring for Remote Machine Learning Postdoc jobs? Cities in Colorado with the most Remote Machine Learning Postdoc job openings:
Remote Machine Learning Postdoc jobs near you
Distinguished AI/ML Engineer

Distinguished AI/ML Engineer

Frontier Technology Inc.

Colorado Springs, CO • On-site, Remote

$190K - $220K/yr

Full-time

Posted 14 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.
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