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Phd Machine Learning Startup Jobs in Colorado (NOW HIRING)

Principal AI/ML Engineer

Englewood, CO · On-site

$75 - $80.15/hr

Master's degree or PhD in Artificial Intelligence, Machine Learning, Computer Science, or a related field. * Experience applying AI/ML to: * Autonomous systems * Sensor fusion * Computer vision

MS or PhD in machine learning, computer science, mathematics, or relevant fields * Experience leading an interdisciplinary team of researchers and software developers * Experience with any of the ...

MS or PhD in machine learning, computer science, mathematics, or relevant fields * Experience leading an interdisciplinary team of researchers and software developers * Experience with any of the ...

Showing results 41-60

Phd Machine Learning Startup information

What are common challenges faced by PhD machine learning professionals in startups?

PhD-level professionals in machine learning startups often encounter challenges such as balancing research innovation with the need for rapid product development. Unlike academia, startups prioritize practical solutions that fit tight deadlines and resource constraints. Team members typically wear multiple hats and collaborate closely with engineers, product managers, and business stakeholders, requiring strong communication skills and adaptability. Additionally, translating cutting-edge research into scalable, real-world applications can be both intellectually rewarding and demanding.

What does a PhD machine learning professional do at a startup?

PhD holders in Machine Learning at startups typically lead research and development efforts to create innovative algorithms and models that solve real-world problems. They often work on designing and implementing advanced machine learning solutions, analyzing large datasets, and collaborating with product and engineering teams to bring research ideas to production. Their expertise helps startups stay competitive by driving technological advancements and fostering a culture of innovation.

What skills and qualifications are needed to thrive as a PhD machine learning professional in a startup?

To excel as a PhD-level Machine Learning professional at a startup, you need advanced expertise in machine learning algorithms, statistical modeling, and a doctoral degree in a related field. Experience with Python, TensorFlow, PyTorch, and version control systems, along with a strong publication record, is typically expected. Initiative, adaptability, and excellent problem-solving and communication abilities are crucial soft skills in the fast-paced startup setting. These competencies enable rapid innovation, effective team collaboration, and successful deployment of machine learning solutions under resource constraints.

What cities in Colorado are hiring for Phd Machine Learning Startup jobs?

Cities in Colorado with the most Phd Machine Learning Startup job openings:

Infographic showing various Phd Machine Learning Startup job openings in Colorado as of June 2026, with employment types broken down into 73% Full Time, 25% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

Staff AI/ML Engineering Manager

CACI International Inc

Aurora, CO • On-site

Full-time

Re-posted 15 days ago


Job description

Job Summary:
CACI International Inc is seeking a talented and motivated AI/ML Engineering Manager to join their growing team. This unique player/coach role involves managing and mentoring a team of skilled AI/ML researchers and engineers while actively applying cutting-edge AI/ML algorithms to meet customer mission needs.
Responsibilities:
• Hands-on AI/ML Development: Actively participate in the end-to-end machine learning lifecycle, contributing high-quality, well-tested, and maintainable code for data pipelines, model training, evaluation, and deployment to key AI/ML projects using our tech stack.Proven proficiency in Python, including experience with key machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy).
• ML System Design & Architecture: Contribute to technical design discussions and architectural decisions for scalable and robust machine learning systems, including data pipelines, model training infrastructure, serving layers, and MLOps frameworks.
• Code & Model Quality: Actively participate in code reviews, ensuring adherence to coding standards, MLOps best practices, and high-quality engineering principles, specifically for machine learning models and infrastructure (e.g., reproducibility, testability, explainability).
• Stay Current and Mentor: Keep abreast of cutting-edge machine learning research, algorithms, MLOps tools, and cloud AI/ML services, advocating for their strategic adoption. Leverage this continuous learning to mentor and provide technical direction to your AI/ML team.
• Lead & Mentor: Manage, coach, and mentor a team of AI/ML engineers, fostering their technical and professional growth, by providing career advice and helping with program technical guidance. Additionally, you will work with the greater AI/ML engineering group to cultivate a positive, collaborative, inclusive, and high-performing team that is focused on bringing modern AI/ML development practices and robust engineering principles across all ARKA programs.
• Performance Management: Conduct regular 1:1 bi-weekly meetings with your team, provide feedback on both technical and non-technical topics, assist with setting clear goals, and manage performance reviews for your direct reports.
• Collaboration: Work closely with AI/ML engineering organization and other engineering leadership to align priorities, define requirements, and ensure successful project delivery across programs.
• Project Oversight: Help manage project priorities, timelines, and deliverables for your team, identifying and removing roadblocks.
• Hiring & Onboarding: Participate in the recruitment, interviewing, onboarding, and retention of engineering talent for your team and the broader organization. Additionally works closely with engineering leadership to align current and new staff skillsets with program needs over time.
Qualifications:
Required:
• Bachelor’s degree in computer science, data science, mathematics, engineering, or a related field
• 3+ years of experience in a formal or informal leadership capacity (e.g., Tech Lead, Team Lead, mentoring junior engineers, project leadership)
• 8+ years of experience developing AI/ML applications, data science, or algorithm development
• Experience with Python and data science / machine learning libraries (e.g. PyTorch, TensorFlow, Keras, OpenCV, NumPy, Pandas, Polars, scikit-learn, etc.)
• Experience with one or more of the following areas: Applying unsupervised and/or supervised machine learning techniques, Applying and/or developing algorithms based in statistical analysis, Analyzing large datasets and building models to perform inference, Applying Large Language Models (LLMs) and techniques such as retrieval augmented generation (RAG), fine tuning, and prompt engineering
• Experience with deep learning architectures (e.g. FCNs, CNNs, RNNs, Transformers, GANs)
• Experience with modern software development methodologies (Agile, Scrum, Kanban)
• Experience with version control systems such as Git and the associated tooling to for modern software version control
• Excellent communication, interpersonal, and collaboration skills
• Strong problem-solving and analytical abilities
• A genuine passion for both technology and people leadership
• Ability to effectively balance management responsibilities with individual technical contributions
• Active TS/SCI U.S. Government Security Clearance
Preferred:
• MS or PhD in machine learning, computer science, mathematics, or related fields
• Experience directly managing AI/ML engineers, including performance management cycles
• Experience with any of the following AI/ML domains: Large Language Models and experience identifying ways to incorporate them into new areas and applications, Applying Transformer-based architectures to domains in other areas outside of Natural Language Processing (NLP) such as computer vision, Object detection algorithms such as YOLO and Faster-RCNN, Natural Language Processing algorithms such as BERT, Generative Adversarial Networks and Variational Autoencoders, Reinforcement learning and familiarity with Gymnasium Gym, RLlib, and Stable Baselines, Applying clustering algorithms and/or deep neural networks to real life problems, Implementing tracking and pattern-of-life algorithms
• Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
• Experience with Computer Vision libraries such as OpenCV, Nerfstudio, FiftyOne, etc.
• Experience with Linux
• Familiarity with using AWS cloud computing resources such as EC2, S3, Lambda, etc.
• Experience with any of the following additional languages: Java, C++, Rust, Go, and/or C#
• Experience implementing algorithms on the GPU in Python or C++ using CUDA and other CUDA libraries
• Experience in application deployment, virtualization, and containerization (e.g. Podman, Docker, Kubernetes, Rancher)
• Experience working with various Remote Sensing datasets (e.g. EO/OPIR/SAR images, passive RF, etc.)
• Experience shaping and writing proposals
Company:
At CACI International Inc (NYSE: CACI), our 27,000 talented and dynamic employees are ever vigilant in delivering distinctive expertise and technology to meet our customers’ greatest challenges in national security. Founded in 1962, the company is headquartered in Arlington, USA, with a team of 10001+ employees. The company is currently Late Stage.