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Phd Machine Learning Startup Jobs in Colorado (NOW HIRING)

As a Senior Data Scientist, you will accelerate our end-to-end machine learning lifecycle, building ... Proven experience working in a fast-paced, agile, or startup-like environment. You must have a ...

Senior Applied AI/ML Scientist

Denver, CO · On-site

$180K - $225K/yr

Most importantly, we are a mission-oriented, high-growth startup and we are looking for folks that ... PhD in AI, Machine Learning or Computer Science preferred * Minimum 4 years of experience in ...

2027 PhD Research Engineering Intern/Co-op

Fort Collins, CO · On-site

$16.50 - $21.50/hr

Whether you're an undergrad or a PhD student, your contributions matter--and your experience here ... design, machine learning) * FPGA or ASIC-based RTL design and verification, FPGA deployment and ...

2027 PhD Research Engineering Intern/Co-op

Longmont, CO · On-site

$16.50 - $21.50/hr

Whether you're an undergrad or a PhD student, your contributions matter--and your experience here ... design, machine learning) * FPGA or ASIC-based RTL design and verification, FPGA deployment and ...

Graduate student (MS or PhD, returning to your program after the co-op) About Apollo Apollo leads ... Strong foundations in modern machine learning, including deep learning, optimization ...

Graduate student (MS or PhD, returning to your program after the co-op) About Apollo Apollo leads ... Strong foundations in modern machine learning, including deep learning, optimization ...

Graduate student (MS or PhD, returning to your program after the co-op) About Apollo Apollo leads ... Strong foundations in modern machine learning, including deep learning, optimization ...

Graduate student (MS or PhD, returning to your program after the co-op) About Apollo Apollo leads ... Strong foundations in modern machine learning, including deep learning, optimization ...

Showing results 41-60

Phd Machine Learning Startup information

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 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.

How much does a PhD in machine learning make?

A PhD in machine learning working at a startup or tech company typically earns between $100,000 and $150,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in deep learning or AI may command higher salaries, especially in competitive markets.

What can you do with a PhD in machine learning?

A PhD in machine learning prepares individuals for advanced roles such as research scientist, machine learning engineer, or data scientist in startups and tech companies. It enables expertise in developing algorithms, analyzing large datasets, and deploying AI models using tools like Python, TensorFlow, or PyTorch. These roles often require strong programming skills, knowledge of statistical methods, and the ability to work on innovative AI solutions.

What are popular job titles related to Phd Machine Learning Startup jobs in Colorado?

For Phd Machine Learning Startup jobs in Colorado, the most frequently searched job titles are:

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.

Protocos | Boulder, CO ; Cambridge, MA USA Senior Machine Learning Scientist, Climate & Hydrology

Boulder, CO • On-site

Flagship Pioneering
Biotechnology Research and Development • 51 - 200 employees

$168K - $231K/yr

Other

Re-posted 5 days ago


Key responsibilities

  • Lead scientific and technical efforts at the intersection of hydrology, climate science, and machine learning.

  • Help define research priorities, modeling directions, and evaluation strategies for climate and environmental prediction systems.

  • Build and oversee reproducible workflows for data processing, model training, benchmarking, and validation.


Job description

Senior Machine Learning Scientist, Climate & Hydrology

Boulder, CO USA; Cambridge, MA USA

Flagship Pioneering is a bioplatform innovation company focused on creating new technologies.

We are seeking a Senior Machine Learning Scientist, Climate and Hydrology to lead the scientific direction and machine learning development for hydrology-aware climate modeling within our broader environmental modeling platform.

This role sits at the intersection of hydrology, weather and climate science, and large-scale machine learning. The Sr. Scientist will help shape how hydrologic process understanding, climate data, and modern ML methods are brought together in next-generation prediction systems, with emphasis on scientifically grounded model development and evaluation.

This individual in this role will work across science, ML, engineering, and data teams to define research priorities, guide model training and benchmarking, build reproducible workflows, and translate scientific insight into scalable model development. This is a cross-functional role requiring strong technical depth, structured scientific thinking, and the ability to move between foundational research and applied execution.

Key Responsibilities
  • Lead scientific and technical efforts at the intersection of hydrology, climate science, and machine learning.
  • Help define research priorities, modeling directions, and evaluation strategies for next-generation climate and environmental prediction systems.
  • Contribute to the development and improvement of ML-based modeling approaches informed by physical and Earth system science.
  • Work with large-scale climate, weather, hydrology, and remote sensing datasets to support model development and scientific analysis.
  • Build and oversee reproducible workflows for data processing, model training, benchmarking, and validation.
  • Collaborate closely with research, engineering, and data teams to translate scientific goals into scalable technical execution.
  • Guide assessment of model performance, uncertainty, and scientific robustness across a range of environmental conditions and applications.
  • Communicate findings through internal reviews, external collaborations, publications, and technical presentations.
  • Help shape the broader scientific roadmap and contribute to team growth and cross-functional leadership.
Professional Experience & Qualifications
  • PhD in machine learning, computational science, Earth science, atmospheric science, hydrology, AI, computer science, or a related quantitative discipline.
  • 5+ years of postdoctoral, industry, or applied research experience in climate ML, weather ML, hydrologic modeling, Earth system modeling, or a closely related field.
  • Demonstrated experience with ML-accelerated weather, climate, or hydrology models, with a strong publication track record in the area.
  • Experience working with large climate datasets, including reanalysis products, remote sensing datasets, observational datasets, and model output.
  • Experience with the computational infrastructure required to manage, preprocess, and train on large-scale climate datasets, preferably in the AWS ecosystem.
  • Strong programming skills in Python and experience with modern ML frameworks such as PyTorch.
  • Background in scientific ML, spatiotemporal modeling, data assimilation, hybrid physics-ML methods, or related approaches is strongly preferred.
  • Ability to design rigorous evaluation frameworks, performance metrics, and benchmarking approaches for environmental prediction systems.
  • Strong technical writing and communication skills, including reports, presentations, and peer-reviewed publications.
  • Demonstrated ability to work independently in fast-paced, ambiguous environments while collaborating effectively across disciplines.
  • Experience leading cross-functional scientific efforts, mentoring researchers, or helping define research roadmaps is preferred.
Location

Cambridge, MA or Boulder, CO (some travel to Cambridge, MA based headquarters if working from Colorado).

Salary: $127,000 - $205,900 (Colorado) and $168,000 - $231,000 (Massachusetts).

We are an equal opportunity employer. All qualified applicants will be considered for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

We recognize that great candidates often bring unique strengths without fulfilling every qualification. If you have some of the experience listed above but not all, please apply anyway. We are dedicated to building diverse and inclusive teams and look forward to learning more about your background and interest in Flagship.

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