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Temporary Machine Learning Scientist Jobs (NOW HIRING)

Senior Machine Learning Scientist

Brisbane, CA ยท On-site +1

$110K - $150K/yr

At Freenome, we are seeking a Senior Machine Learning Scientist to help grow the Machine Learning Science team, within the Computational Science department. The ideal candidate has a strong knowledge ...

Staff Machine Learning Scientist

Brisbane, CA ยท On-site +1

$199K - $283K/yr

At Freenome, we are seeking a Staff Machine Learning Scientist to help grow the Machine Learning Science team, within the Computational Science department. The ideal candidate has a strong knowledge ...

Staff Machine Learning Scientist

Brisbane, CA ยท On-site

$199K - $283K/yr

At Freenome, we are seeking a Staff Machine Learning Scientist to help grow the Machine Learning Science team, within the Computational Science department. The ideal candidate has a strong knowledge ...

Machine Learning Scientist, BioML

Emeryville, CA ยท On-site +1

$200K - $330K/yr

We're looking for a motivated and creative Machine Learning (ML) Scientist to drive research into models at the intersection of complex protein biology and AI. This position offers an opportunity to ...

Sr Machine Learning Scientist

Thousand Oaks, CA ยท On-site +1

$96K - $131K/yr

Machine Learning Scientist What you will do Let's do this. Let's change the world. Within Amgen's Research and Development organization, the Therapeutic Protein Design (TPD) team supports the broad ...

Senior Machine Learning Scientist

Austin, TX ยท On-site

$97K - $124K/yr

DISCO is a company providing AI-powered legal solutions, and they are seeking a Senior Machine Learning Scientist to lead their machine learning and AI research initiatives. This role involves ...

Senior Machine Learning Scientist

Salt Lake City, UT ยท On-site

$88K - $121K/yr

Senior Machine Learning Scientist (Surrogate modeling & decision science in the earth sciences) Hours: Full-Time, Salaried Location: Salt Lake City, UT, Hybrid (3 days in office, 2 days can be remote ...

Senior Machine Learning Scientist

Salt Lake City, UT ยท On-site +1

$88K - $121K/yr

Senior Machine Learning Scientist (Surrogate modeling & decision science in the earth sciences) Hours: Full-Time, Salaried Location: Salt Lake City, UT, Hybrid (3 days in office, 2 days can be remote ...

Machine Learning Scientist What you will do Let'sdo this.Let'schange the world.Within Amgen's Research and Development organization, the Therapeutic Protein Design (TPD) team supports the broad goal ...

Senior Machine Learning Scientist

Boston, MA ยท On-site

$99K - $135K/yr

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI team, focusing on AI applications (LLM and Computer Vision) in Cloud, Devices and Robotics. As a ...

Senior Machine Learning Scientist

Seattle, WA ยท On-site

$104K - $142K/yr

Your Impact We are seeking highly skilled and innovative Machine Learning Scientists to join our AI team, focusing on AI applications (LLM and Computer Vision) in Cloud, Devices and Robotics. As a ...

Senior Machine Learning Scientist

Salt Lake City, UT ยท On-site +1

$88K - $121K/yr

Senior Machine Learning Scientist (Surrogate modeling & decision science in the earth sciences) Hours: Full-Time, Salaried Location: Salt Lake City, UT, Hybrid (3 days in office, 2 days can be remote ...

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Showing results 1-20

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 are Temporary Machine Learning Scientists?

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.
More about Temporary Machine Learning Scientist jobs
What cities are hiring for Temporary Machine Learning Scientist jobs? Cities with the most Temporary Machine Learning Scientist job openings:
What are the most commonly searched types of Machine Learning Scientist jobs? The most popular types of Machine Learning Scientist jobs are:
What states have the most Temporary Machine Learning Scientist jobs? States with the most job openings for Temporary Machine Learning Scientist jobs include:
Infographic showing various Temporary Machine Learning Scientist job openings in the United States as of June 2026, with employment types broken down into 6% Internship, 88% Full Time, and 6% Contract. Highlights an 79% In-person, 3% Hybrid, and 18% Remote job distribution.
Senior Machine Learning Scientist

Senior Machine Learning Scientist

Freenome

Brisbane, CA โ€ข On-site, Remote

$110K - $150K/yr

Other

Posted 20 days ago


Job description

About this opportunity:

At Freenome, we are seeking a Senior Machine Learning Scientist to help grow the Machine Learning Science team, within the Computational Science department. The ideal candidate has a strong knowledge of artificial intelligence (AI), including machine learning (ML) fundamentals and extensive experience with deep learning (DL) methods, a track record of successfully using these methods to answer complex research questions, and the ability to thrive in a highly cross-functional environment.

They will be responsible for the development of algorithms for early, blood-based detection tests for cancer. They will build on a foundation of ML/DL and statistical skills to develop models for identifying molecular signals from blood. They will also work with computational biologists, molecular biologists and ML engineers to design and drive research experiments, and will have a significant impact on the continued growth of an organization dedicated to changing the entire landscape of cancer.

The role reports to the Director, Machine Learning Science. This role can be a Hybrid role based in our Brisbane, California headquarters (2-3 days per week in office), or remote.

What you'll do:

  • Independently pursue cutting edge research in AI applied to biological problems (including cancer research, genomics, computational biology, immunology, etc.).
  • Build new models or fine-tune existing models to identify biological changes resulting from disease.
  • Build models that achieve high accuracy and that generalize robustly to new data.
  • Apply contemporary interpretability techniques to provide a deeper understanding of the underlying signal identified by the model, ideally suggesting potential biological mechanisms.
  • Work closely with ML Engineering partners to ensure that Freenome's computational infrastructure supports optimal model training and iteration.
  • Take a mindful, transparent, and humane approach to your work.

Must haves:

  • PhD or equivalent research experience with an AI emphasis and in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Computational Biology, or Bioinformatics.
  • 3+ years of postdoc or post-PhD industry experience achieving impactful results using relevant modeling techniques.
  • Expertise, demonstrated by research publications or industry achievements, in applied machine learning, deep learning and complex data modeling.
  • Practical and theoretical understanding of fundamental ML models like generalized linear models, kernel machines, decision trees and forests, neural networks.
  • Practical and theoretical understanding of DL models like large language models or other foundation models.
  • Extensive experience with training paradigms like supervised learning, self-supervised learning, and contrastive learning.
  • Proficient in current state of the art in ML/DL approaches in different domains, with an ability to envision their applications in biological data.
  • Proficiency in a general-purpose programming language: Python, R, Java, C, C++, etc.
  • Proficiency in one or more ML frameworks such as; Pytorch, Tensorflow and Jax; and ML platforms like Hugging Face.
  • Experience in ML analysis and developer tools like TensorBoard, MLflow or Weights & Biases.
  • Excellent ability to communicate across disciplines, work collaboratively, and make progress in smaller steps via experimental iterations.
  • A passion for innovation and demonstrated initiative in tackling new areas of research.

Nice to haves:

  • Deep domain-specific experience in computational biology, genomics, proteomics or a related field.
  • Experience in building DL models for genomic data, with knowledge of state-of-the-art DNA foundation models.
  • Experience in NGS data analysis and bioinformatic pipelines.
  • Experience with containerized cloud computing environments such as Docker in GCP, Azure, or AWS.
  • Experience in a production software engineering environment, including the use of automated regression testing, version control, and deployment systems.

Benefits and additional information:

The US target range of our base salary/hourly rate for new hires is $173,775 - $246,750. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.ย  Please note that individual total compensation for this position will be determined at the Company's sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ย for additional company information.ย ย 

Freenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Applicants have rights under Federal Employment Laws.ย ย 

  • Family & Medical Leave Act (FMLA)
  • Equal Employment Opportunity (EEO)
  • Employee Polygraph Protection Act (EPPA)

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