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Machine Learning Biomedical Engineer Jobs in Minnesota

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 ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Showing results 41-60

Machine Learning Biomedical Engineer information

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.

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 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.

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 cities in Minnesota are hiring for Machine Learning Biomedical Engineer jobs?

Cities in Minnesota with the most Machine Learning Biomedical Engineer job openings:

Infographic showing various Machine Learning Biomedical Engineer job openings in Minnesota as of September 2026, with employment types broken down into 100% Full Time. Highlights an 86% In-person, and 14% Remote job distribution.

Development Engineer/LEAD MACHINE LEARNING ENGINEER

Minneapolis, MN โ€ข On-site

UrBench
Recruiting and Staffing Servicesย โ€ขย 1 - 10 employees

$65 - $70/hr

Contractor

Re-posted yesterday


Job description

Local candidates only
Must have local project in recent/Local DL copy
Overall 7+ years of exp
Visa - OPT/CPT/H4 EAD/Gc EAD/L2 EAD/USC/GC only
Rate - $65-70/hr W2 + $7 referral, open for higher rate based on their exp.
Client - TARGET
Location - Minneapolis, MN - Hybrid 2 days onsite
Role - Development Engineer/LEAD MACHINE LEARNING ENGINEER
Duration - 6-12 months contract with long term extension
Must Have:
Kaftka
Machine Learning
Machine Learning Development
Python, Pyspark or Scala
SPARK
Nice to Have:
Java
AS A LEAD MACHINE LEARNING ENGINEER
About Us:
Join our global in-house Tech and Data Sciences team
As Lead Machine Learning Engineer, you will join a Data Sciences team responsible for creating personalized recommendations on Target.com and the Target App. You will play a crucial role in designing, implementing, and optimizing production machine learning solutions. We will also expect you to understand best practice software design, participate in code reviews, and create a maintainable well-tested codebase with relevant documentation. At an organizational level, you will conduct training sessions, present work to technical and non-technical peers/leaders, build knowledge on business priorities/strategic goals and leverage this knowledge while building requirements and solutions for each business need.
Core responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs.
Qualifications:
  • 4-year degree in Quantitative disciplines (Science, Technology, Engineering, Mathematics) or equivalent experience
  • MS in Computer Science, Applied Mathematics, Statistics, Physics or equivalent work or industry experience
  • 5 plus years' experience in end-to-end Machine Learning application development, including data pipelining, model optimization, deployment, and API design
  • Highly proficient programming in Python and either PySpark or Scala
  • Experience with ML frameworks such as Pytorch, TensorFlow, xgboost, sklearn, and ONNX
  • Experience with one or more cloud ML services such as Vertex AI/Azure ML/Sagemaker
  • Experience using distributed training frameworks like Spark/Ray/TensorFlow Distribute
  • Experience with serving frameworks such as TorchServe/TensorFlow Serving/FastAPI
  • Good understanding of Big Data tech, specifically Kafka, Spark
  • Experience creating and maintaining CI/CD pipelines for automated model deployment and testing
  • Work in partnership with data scientists, software engineers and product managers to understand the business requirements and translate to machine learning solutions at scale
  • Excellent communication skills with the ability to clearly tell data driven stories through appropriate visualizations, graphs, and narratives
  • Self-driven and results oriented; able to meet tight timelines
  • Ability to collaborate effectively across global team
  • Experience in mentoring the junior team members ML skillset and career development
Nice to Have:
  • PhD in Computer Science, Applied Mathematics, Statistics, Physics or related quantitative field
  • Proficiency in Java
  • This position will operate as a Hybrid/Flex for Your Day work arrangement based on ***'s needs. A Hybrid/Flex for Your Day work arrangement means the team member's core role will need to be performed both onsite at the *** HQ location the role is assigned to and virtually, depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by ***.
  • Onsite 1 day a week at minimum. Sometimes teams may require up to 3 days and full Core Weeks attendance.

UrBench is an equal opportunity employer and is committed to creating a diverse environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, pregnancy, status as a parent, disability, age, veteran status, or other characteristics as defined by federal, state or local laws.


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About UrBench

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Nurturing Excellence in the USA Since 2000 Hello, fellow explorer! Welcome to UrBench, where American excellence and expertise have been thriving since 2000. Get ready for a journey beyond the ordinary, because we're not your typical recruitment and staffing company. We're more like the architects of achievement, the conductors of compatibility, and the champions of collaboration right here in the States. Our High Skilled Team Players UrBench's adept team forge success by linking talent and opportunities with integrity and innovation. They empower individuals and organizations, propelling our mission forward. Our Expertise & Skills to All Business Because we're not just another company โ€“ we're your backstage pass to success, deeply rooted in the heart of the USA. With us, you're not a client; you're a collaborator, a co-pilot, and a fellow visionary in the quest for greatness on American soil. From tech revolutions to industry shifts, we've been here, shaping the landscape and creating success stories. Let's embark on this journey together, crafting history, one exceptional partnership at a time.

Industry

Recruiting and staffing services

Company size

1 - 10 Employees

Headquarters location

Austin, TX, US