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Machine Learning Biomedical Engineer Jobs in Utah

Machine Learning Engineer At Leash Biosciences, we are at the cutting edge of integrating machine learning with drug discovery. Our unique approach focuses on predicting molecular and protein ...

Senior Machine Learning Engineer

Draper, UT

$97K - $134K/yr

As a Senior Machine Learning Engineer , you'll play a pivotal role in designing, building, and deploying machine learning solutions that power BILL's next-generation products. This is an opportunity ...

Senior Machine Learning Engineer

Draper, UT · On-site

$114K - $151K/yr

As a Senior Machine Learning Engineer, you will design, build, and deploy machine learning solutions that enhance BILL's products and directly impact user experiences. Responsibilities : • Design ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Biomedical Engineering tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have ...

About the Job The Varsity Tutors Live Learning Platform has thousands of students looking for online Biomedical Engineering tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have ...

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Machine Learning Biomedical Engineer information

What is the difference between Machine Learning Biomedical Engineer vs Data Scientist in Biomedical Industry?

AspectMachine Learning Biomedical EngineerData Scientist in Biomedical Industry
Required CredentialsDegree in Biomedical Engineering, Computer Science, or related fields; knowledge of machine learning and biomedical dataDegree in Data Science, Statistics, or related fields; proficiency in data analysis and machine learning
Work EnvironmentResearch labs, healthcare institutions, biotech companiesHealthcare analytics firms, research institutions, biotech companies
Employer & Industry UsageDevelops algorithms for medical devices, diagnostics, and treatment planningAnalyzes biomedical data to inform clinical decisions, research, and product development

Both roles require expertise in machine learning and biomedical data, but Machine Learning Biomedical Engineers focus on developing algorithms for medical applications, while Data Scientists analyze biomedical data to support research and clinical decisions.

What does a Machine Learning Biomedical Engineer do?

A Machine Learning Biomedical Engineer applies machine learning techniques to solve problems in biology and medicine. They develop algorithms and models to analyze complex biomedical data, such as medical images, genetic information, or sensor readings. Their work supports advancements in diagnostics, treatment planning, and personalized medicine. Typically, they collaborate with clinicians, researchers, and other engineers to design systems that improve healthcare outcomes.

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

To thrive as a Machine Learning Biomedical Engineer, you need a strong background in biomedical engineering, data analysis, and machine learning, typically supported by a degree in biomedical engineering, computer science, or a related field. Familiarity with programming languages like Python or R, machine learning frameworks (e.g., TensorFlow, PyTorch), and experience with medical imaging or signal processing tools are commonly required. Critical thinking, problem-solving, and the ability to communicate complex technical concepts to interdisciplinary teams are vital soft skills. These abilities are crucial for developing innovative healthcare solutions, ensuring regulatory compliance, and bridging the gap between technology and medicine.

How does a Machine Learning Biomedical Engineer typically collaborate with clinicians and researchers in a healthcare setting?

Machine Learning Biomedical Engineers often work closely with clinicians and researchers to develop algorithms that solve real-world medical challenges. Collaboration usually involves understanding clinical needs, translating them into technical requirements, and iteratively refining models based on feedback from medical experts. Regular meetings, interdisciplinary project teams, and direct participation in data collection or validation studies are common. This collaborative environment ensures that technical solutions are both innovative and clinically relevant, making communication and adaptability essential skills.
What are popular job titles related to Machine Learning Biomedical Engineer jobs in Utah? For Machine Learning Biomedical Engineer jobs in Utah, the most frequently searched job titles are:
What cities in Utah are hiring for Machine Learning Biomedical Engineer jobs? Cities in Utah with the most Machine Learning Biomedical Engineer job openings:

Machine Learning Engineer

Leash Bio

Salt Lake City, UT

$150K - $200K/yr

Other

Medical, Retirement

Posted 13 days ago


Job description

Machine Learning Engineer

At Leash Biosciences, we are at the cutting edge of integrating machine learning with drug discovery. Our unique approach focuses on predicting molecular and protein interactions, aiming to revolutionize the field of medicinal chemistry. Our team prides itself on its ability to generate and analyze vast datasets, directly contributing to groundbreaking advancements in drug development.

We offer a supportive and inclusive environment, encouraging personal agency, collaboration, and sharing of knowledge. We're driven by an ambitious goal, and we aim to inspire each other to achieve groundbreaking results. We take big bets and are okay when only some of them pay off.

Benefits include healthcare, 401K match, stock options, free lunches, and access to some of the best outdoor locations in the country.

The Role:

We are seeking a highly skilled and self-driven Machine Learning Engineer to join our team. In this role, you'll be instrumental in handling enormous datasets, orchestrating cloud-based computing resources, and training a multitude of advanced machine-learning models. Your work will directly contribute to our mission of creating foundational models for medicinal chemistry. While you will be dealing with massive amounts of chemical and biological information, biology and chemistry experience is not required. Our dataset can be thought of as billions of labeled sentences so experience with language models is highly relevant.

Key Responsibilities:
  • Manage and optimize data processing workflows for large-scale datasets, with an approach akin to language data handling.
  • Scale and maintain machine learning model training processes, with a focus on cloud environments (primarily Google Cloud, with flexibility to other platforms).
  • Collaborate closely with ML researchers, data scientists, and lab automation teams to ensure seamless integration of lab data and ML model training.
  • Innovate and iterate on our existing technology stack, taking the initiative to solve problems and improve our ML operations.
  • Act as a self-sufficient project manager, overseeing your projects from conception to completion.
About You:
  • Strong experience in machine learning engineering, including data handling, model training, and scaling in cloud environments.
  • Comfortable building ML infrastructure
  • Experience working with large amounts of text data, NLP, or training LLMs
  • Demonstrated capability to make informed decisions, take ownership of solutions, and drive projects forward in a startup environment.
  • Excellent collaboration skills, with the ability to work effectively with cross-functional teams.
Preferred Qualifications:
  • Familiarity with common MLops tooling (e.g., Dagster, Prefect, Airflow, Docker, MLflow, Kubeflow, W&B, Ray, etc.)
  • Ability to manage own compute cluster
  • Ability to maximize GPU utilization and keep cluster busy 24/7
  • Ability to analyze model results and kick off new experiments in response
  • Experience with BERT or similar language models in PyTorch.
  • Experience or interest in biology, chemistry, or related fields is a plus.

Salary: $150,000 - $200,000 per year