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Scientific Machine Learning Jobs in Colorado (NOW HIRING)

Ibotta

Staff Machine Learning Engineer

Denver, CO · On-site +1

$206K - $230K/yr

Mentor ML Engineers and Data Scientists, fostering a culture of technical ownership, rigorous ... Machine Learning Engineer or Software Engineer, focused on deploying machine learning systems at ...

Ibotta

$206K - $230K/yr

Mentor ML Engineers and Data Scientists, fostering a culture of technical ownership, rigorous ... Machine Learning Engineer or Software Engineer, focused on deploying machine learning systems at ...

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All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in Colorado

Scientific Machine Learning information

Is ML a high paying job?

Scientific Machine Learning roles typically offer high salaries due to the specialized skills required, such as expertise in deep learning, data analysis, and programming with tools like Python and TensorFlow. Compensation varies by industry, experience, and location but generally exceeds average tech salaries for comparable roles.

Which 3 jobs will survive AI?

Scientific Machine Learning professionals will likely continue to be in demand due to their expertise in developing and applying AI models to complex scientific problems. Roles such as data scientists, AI researchers, and machine learning engineers are expected to persist because they require specialized knowledge, critical thinking, and ongoing innovation that AI tools complement rather than replace. These jobs often involve interdisciplinary skills, programming, and understanding of domain-specific data, making them more resilient to automation.

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are some common challenges faced by professionals in Scientific Machine Learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

How much does a machine learning scientist make?

A machine learning scientist typically earns between $90,000 and $150,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in deep learning or natural language processing can earn higher salaries, often exceeding $180,000.

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

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

Is 40 too late for data science?

Scientific Machine Learning roles often value skills and experience over age, and many professionals transition into data science or machine learning at various stages of their careers. Learning relevant tools like Python, TensorFlow, or scikit-learn and gaining practical experience can help regardless of age, making 40 not too late to pursue this field.
What are popular job titles related to Scientific Machine Learning jobs in Colorado? For Scientific Machine Learning jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in Colorado look for? The top searched job categories for Scientific Machine Learning jobs in Colorado are:
Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Colorado as of June 2026, with employment types broken down into 78% Full Time, and 22% Part Time. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution.
Lead Machine Learning / Data Science Engineer

Lead Machine Learning / Data Science Engineer

CapTech Consulting

Denver, CO

$57.50 - $76/hr

Other

Medical, Retirement, PTO

Posted 13 days ago

Job description

Company Description
CapTech is an award-winning consulting firm that collaborates with clients to achieve what's possible through the power of technology. At CapTech, we're passionate about the work we do and the results we achieve for our clients. From the outset, our founders shared a collective passion to create a consultancy centered on strong relationships that would stand the test of time. Today we work alongside clients that include Fortune 100 companies, mid-sized enterprises, and government agencies, a list that spans across the country.
Job Description
CapTech Machine Learning Engineers are responsible for designing and implementing data-driven solutions for our clients, with a specific focus on building and deploying scalable machine learning systems in enterprise environments. CapTech employees enjoy a collaborative environment and have many opportunities to learn from and share knowledge with other CapTech analysts, architects, and our clients.
Specific responsibilities for the Lead Machine Learning Engineer position include:
  • Strategizing with clients, data scientists, engineers, and other members of cross-functional teams to implement end-to-end machine learning solutions and identify new machine learning and data science approaches to meet business needs
  • Provide technical leadership and collaborate within and across teams to ensure that the overall technical solution is aligned with the customer needs.
  • Deconstructing client needs into data-driven processes/models and analytical measures.
  • Analyzing and transforming large datasets hosted on a variety of enterprise-level data platforms (e.g., AWS, Azure, GCP).
  • Designing, developing, and deploying advanced analytical solutions leveraging client data (e.g., recommender systems, natural language processing, risk scoring).
  • Productionizing ML systems with a focus on optimization and scalability to satisfy clients' requirements.
  • Growing CapTech's Machine Learning and Data Science practices through delivering client presentations, writing proposals, attending various business development events, and leading teams of junior data scientists and engineers.
Qualifications
  • 7+ years of experience delivering data engineering and machine learning solutions on cloud platforms
  • Bachelor's degree or equivalent combination of education and experience.
  • Experience providing technical leadership and mentoring other engineers in data engineering space
  • Hands-on experience manipulating and analyzing large (multi-billion record) data sets.
  • Hands-on experience developing data-driven solutions using Python, Scala, or similar languages.
  • Proficiency leveraging SQL, Spark, NoSQL, and/or cloud data processing frameworks in a production setting.
  • Proficiency with containerization (e.g., Docker) and microservices.
  • Proficiency with data warehousing tools/environments such as Snowflake, Databricks, Azure SQL, Amazon RDS
  • Comfort and proficiency in framing data-driven problems from cross-industry business requirements.
  • Experience applying analytical methods across multiple business domains (e.g., customer analytics, marketing, finance, digital channels)
  • Hands-on experience implementing production-scale machine learning systems in one or more domains (i.e., personalization, natural language processing, computer vision).
  • Knowledge of DevOps and automation best practices.
  • Knowledge of statistics and statistical modeling methods.
  • Knowledge of model management and model versioning best practices.
  • Experience working with LLMs (e.g., GPT, Claude, Mistral, etc.) in production setting
  • Experience with prompt engineering, MCP and RAG, and agentic AI architectures
  • Strong understanding of conversational UX and prompt evaluation metrics
  • Experience with agentic frameworks in practice (langchain, n8n, pydantic, etc.)
  • Experience with multi-agent orchestration
Additional Information
We want everyone at CapTech to be able to envision a lasting and rewarding career here, which is why we offer a variety of career paths based on your skills and passions. You decide where and how you want to develop, and we help get you there with customizable career progression and a comprehensive benefits package to support you along the way. Alongside our suite of traditional benefits encompassing generous PTO, health coverage, disability insurance, paid family leave and more, we've launched extended benefits to help meet our employees' needs.
  • CapTech is committed to providing a flexible work environment and helping our employees achieve a work-life balance that suits their individual needs. Employees must be available to work onsite in a client location or a CapTech office as requested. We allow CapTech employees to work remotely when compatible with CapTech and client needs.
  • Learning & Development - Programs offering certification and tuition support, digital on-demand learning courses, mentorship, and skill development paths
  • Modern Health -A mental health and well-being platform that provides 1:1 care, group support sessions, and self-serve resources to support employees and their families through life's ups and downs
  • Carrot Fertility -Inclusive fertility and family-forming coverage for all paths to parenthood - including adoption, surrogacy, fertility treatments, pregnancy, and more - and opportunities for employer-sponsored funds to help pay for care
  • Fringe -A company paid stipend program for personalized lifestyle benefits, allowing employees to choose benefits that matter most to them - ranging from vendors like Netflix, Spotify, and GrubHub to services like student loan repayment, travel, fitness, and more
  • Employee Resource Groups - Employee-led committees that embrace and incorporate diversity and inclusion into our day-to-day operations
  • Philanthropic Partnerships - Opportunities to engage in partnerships and pro-bono projects that support our communities.
  • 401(k) Matching - Generous matching and no vesting period to help you continue to build financial wellness

CapTech is an equal opportunity employer committed to fostering a culture of equality, inclusion and fairness - each foundational to our core values. We strive to create a diverse environment where each employee is encouraged to bring their unique ideas, backgrounds and experiences to the workplace. For more information about our Diversity, Inclusion and Belonging efforts, click HERE. As part of this commitment, CapTech will ensure that persons with disabilities are provided reasonable accommodations. If reasonable accommodation is needed to participate in the job application or interview process, to perform essential job functions, and/or to receive other benefits and privileges of employment, please contact Laura Massa directly via email lmassa@captechconsulting.com.
CapTech supports Equal Pay for all. In addition, in the State of Colorado, we are committed to Equal Pay for ALL in accordance with the Colorado Equal Pay for Equal Work Act. The base pay range for this role is: $90,000 - $200,000.
At this time, CapTech cannot transfer nor sponsor a work visa for this position. Applicants must be authorized to work directly for any employer in the United States without visa sponsorship.

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