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Phd Machine Learning Startup Jobs in Colorado (NOW HIRING)

Judi Health

Machine Learning Engineer

Denver, CO · Remote

Most importantly, we are a mission-oriented, high-growth startup and we are looking for folks that ... Develop and productionize machine learning (ML) solutions in the fields of Document understanding ...

True Anomaly

Senior Machine Learning Engineer

Denver, CO · On-site

$107.50K - $147.70K/yr

Preferred : • Master's or PhD in machine learning, computer science, data science, or a related discipline • Strong background in one of the following core ML disciplines: Anomaly & outlier ...

True Anomaly

Senior Machine Learning Engineer

Denver, CO · On-site

$155K - $260K/yr

Master's or PhD in machine learning, computer science, data science, or a related discipline * Strong background in one of the following core ML disciplines: * Anomaly & outlier detection ...

Cisco

Principal Machine Learning Engineer

Denver, CO · On-site

The Principal Machine Learning Engineer will define the vision for AI across platforms, lead the ... Required : • PhD in Computer Science, or related quantitative field, plus 7+ years of industry ...

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Signifyd

Senior Machine Learning Engineer I // II

Denver, CO · On-site +1

$107.60K - $147.70K/yr

The Senior Machine Learning Engineer will join our ML team. This team is responsible for building ... A Master's Degree or PhD. Why Join Us? * Make an Impact - Your work will directly shape the future ...

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What are the key skills and qualifications needed to thrive as a PhD-level Machine Learning professional in a startup environment, and why are they important?

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 are some common challenges faced by PhD-level professionals working in machine learning 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 do PhD holders in Machine Learning do at startups?

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.
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Phd Machine Learning Startup jobs near you
Infographic showing various Phd Machine Learning Startup job openings in Colorado as of May 2026, with employment types broken down into 28% Internship, and 72% Full Time. Highlights an 67% In-person, and 33% Remote job distribution.

Machine Learning Engineer

Judi Health

Denver, CO • Remote

Other

Posted 22 days ago

Job description

Position Summary: 

Join our mission to infuse cutting-edge AI/ML/GenAI into pharmacy benefits as a Machine Learning Engineer.  We are looking for a software engineer with machine learning expertise to join us in expanding our AI capabilities, enabling increased productivity and magical experiences in our products and services. 

In this role you will be expected to design and implement complex AI systems that leverage ML models for NLP, NLG, multimodal data analysis, chatbots, and RAG-based QnA. The ideal candidate should be passionate about applying AI/ML concepts to difficult problems and develop scalable solutions. We want people who like working in a collaborative team environment and enjoy creating practical, efficient, and high-performance software that leverages Large Language Models (LLM), Multimodal Language Models(MLM), and other ML models and techniques to build amazing capabilities for our customers, partners, and employees. Most importantly, we are a mission-oriented, high-growth startup and we are looking for folks that are excited to be part of our journey to make lasting impact towards transforming healthcare. 

Responsibilities: 

  • Develop and productionize machine learning (ML) solutions in the fields of Document understanding, Search and QnA, GenAI, Virtual Agents, etc. 
  • Develop and maintain backend services using Python, focusing on AI-driven applications. 
  • Design and implement APIs for seamless integration with AI models and services. 
  • Develop tools for large-scale data processing and ETL and contribute to extracting insights from data to help guide ML systems development 
  • Participate in code reviews, testing, and quality assurance processes. 
  • Troubleshoot and resolve technical issues related to AI model, integration, deployment and backend services. 
  • Develop algorithms to ensure the integrity and robustness of ML solutions by developing automated testing and validation processes. 
  • Document and communicate development processes and implementation details with peers and supervisors 
  • Ensure the security and compliance of healthcare data, adhering to HIPAA regulations. 

Required Qualifications: 

  • Bachelor's or Master's degree in Computer Science, Machine Learning, or a related quantitative field. 
  • 2+ years experience in the industry with a strong focus on ML solutions development and production deployment is a plus. 
  • Good understanding of Machine Learning fundamentals such as Deep Neural Networks, Transformer-based LLM and MLMs, Boosted or standard decision trees, RAG, etc.  
  • Strong grasp of OOP, Design Patterns, efficient algorithms, and quality software development. 
  • Proficiency in Python and familiarity with ML libraries such as PyTorch. 
  • Familiarity with GenAI services such as OpenAI GPT, Anthropic Claude, Google Gemma etc. Some experience in developing and fine-tuning prompts on any of the GenAI services is a plus. 
  • Excellent problem-solving skills, attention to detail, and a strong capacity for logical thinking. 
  • The ability to work collaboratively across multiple disciplines in an extremely fast-paced, startup environment. 
  • Good written communication skills that enable collaboration in a remote environment. 

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