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Temporary Machine Learning Scientist Jobs in Colorado

The Role 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 ...

The Role 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 ...

Senior Machine Learning Scientist

Boulder, CO · On-site +1

$96K - $131K/yr

The Role 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 ...

Senior Machine Learning Scientist

Boulder, CO · On-site +1

$96K - $131K/yr

The Role 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 ...

Machine Learning Engineer LOCATION Aurora, CO 80014 CLEARANCE TS/SCI Full Poly (Please note this ... You will collaborate with data scientists, engineers, and product teams to turn data into ...

Ibotta is seeking a Principal Machine Learning Engineer to join our Core Data & Analytics team and ... Mentor ML Engineers and Data Scientists, fostering a culture of technical ownership, rigorous ...

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Temporary Machine Learning Scientist information

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

AspectTemporary Machine Learning ScientistData Scientist
CredentialsTypically requires a master's or PhD in computer science, data science, or related fields; experience with machine learning frameworksUsually holds a bachelor's or master's in data science, statistics, or related fields; strong analytical skills
Work EnvironmentProject-based, often contract roles in tech, finance, or healthcare companiesFull-time or contract roles across various industries, focusing on data analysis and insights
Employer UsageHired for specialized machine learning projects, prototypes, or research tasksEngaged in data analysis, reporting, and building predictive models

In summary, a Temporary Machine Learning Scientist focuses on developing and implementing machine learning models on a temporary basis, often requiring advanced credentials and specialized skills. In contrast, a Data Scientist has a broader role in analyzing data and generating insights, with less emphasis solely on machine learning techniques.

What is a temporary machine learning scientist?

Temporary Machine Learning Scientists are professionals hired on a short-term basis to develop, implement, and optimize machine learning models within an organization. They typically work on specific projects or to fill a temporary gap in expertise, often collaborating with data scientists, engineers, and stakeholders. Their responsibilities may include data preprocessing, feature engineering, model selection, and evaluation. These roles are ideal for projects with defined timelines or exploratory research that does not require a permanent hire. Temporary contracts can range from a few months to a year, depending on the project's scope and needs.

What types of projects do temporary machine learning scientists typically work on, and how do they integrate with existing teams?

Temporary Machine Learning Scientists are often brought in to support short-term projects such as data analysis, model prototyping, or improving existing machine learning pipelines. Their work usually involves collaborating closely with data engineers, software developers, and product managers to ensure seamless integration of models into production systems. Since the role is temporary, effective communication and quick adaptation to the team's workflow are crucial. These scientists are expected to rapidly understand the company's data and objectives, deliver actionable insights, and document their work for team continuity after their contract ends.

What are the key skills and qualifications needed to thrive as a temporary machine learning scientist, and why are they important?

To thrive as a Temporary Machine Learning Scientist, you typically need advanced knowledge of machine learning algorithms, data analysis, programming skills (such as Python or R), and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and tools for data processing and model deployment is often required, along with experience using cloud platforms such as AWS or Azure. Strong problem-solving abilities, adaptability, and effective communication skills help you quickly integrate into teams and deliver results on short-term projects. These skills ensure you can efficiently contribute to impactful solutions and adapt to rapidly changing project requirements.
What are the most commonly searched types of Machine Learning Scientist jobs in Colorado? The most popular types of Machine Learning Scientist jobs in Colorado are:
What are popular job titles related to Temporary Machine Learning Scientist jobs in Colorado? For Temporary Machine Learning Scientist jobs in Colorado, the most frequently searched job titles are:
What cities in Colorado are hiring for Temporary Machine Learning Scientist jobs? Cities in Colorado with the most Temporary Machine Learning Scientist job openings:
Infographic showing various Temporary Machine Learning Scientist job openings in Colorado as of August 2026, with employment types broken down into 20% Internship, and 80% Full Time. Highlights an 60% In-person, and 40% Remote job distribution.

Machine Learning Scientist

3M HEALTHCARE

Boulder, CO • On-site, Remote

Full-time

Medical, Retirement

This job post has expired today. Applications are no longer accepted.


Job description

Company Description Flagship Pioneering is a bioplatform innovation company that invents and builds companies that change the world. We bring together the greatest scientific minds with entrepreneurial company builders and assemble the capital to allow them to take courageous leaps. Those big leaps in human health, sustainability and beyond exponentially accelerate scientific progress in areas ranging from disease detection and treatment and nature-positive agriculture to novel applications of AI that are driving the creation of new technologies. What sets Flagship apart is our ability to advance science and technology by uniting innovation, company creation, and capital investment under one roof in a way that is largely without precedent. Our scientific founders, entrepreneurial leaders, and professional capital managers are each aligned around an institutionalized process that enables us to innovate and transform for the benefit of people and planet. Many of the companies Flagship has founded have addressed humanity's most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture. Flagship has been recognized twice on FORTUNE's "Change the World" list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies, and has been twice named to Fast Company's annual list of the World's Most Innovative Companies. The Role 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. The 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). About Flagship Pioneering Flagship Pioneering invents and builds platform companies, each with the potential for multiple products that transform human health, sustainability and beyond. Since its launch in 2000, Flagship has originated more than 100 companies. Many of these companies have addressed humanity's most urgent challenges: vaccinating billions of people against COVID-19, curing intractable diseases, improving human health, preempting illness, and feeding the world by improving the resiliency and sustainability of agriculture. Flagship has been recognized twice on FORTUNE's "Change the World" list, an annual ranking of companies that have made a positive social and environmental impact through activities that are part of their core business strategies and has been twice named to Fast Company's annual list of the World's Most Innovative Companies. Learn more about Flagship at www.flagshippioneering.com. At Flagship, we accept impossible missions to enable bigger leaps. Our core values guide us through uncertainty and toward lasting impact. Equal Opportunity Employer 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. Salary and Benefits The salary ranges for this role are $127,000 - $205,900 (Colorado) and $168,000 - $231,000 (Massachusetts). Compensation for the role will depend on a number of factors, including a candidate's qualifications, skills, competencies, and experience. Protocos currently offers healthcare coverage, annual incentive program, retirement benefits and a broad range of other benefits. Compensation and benefits information is based on Protoco's good faith estimate as of the date of publication and may be modified in the future. #J-18808-Ljbffr