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Machine Learning Biomedical Engineer Jobs in New Jersey

As a Machine Learning Engineer, you will play a critical role in shaping the future of cooking. Working on a small, high-impact team, you will have significant ownership over the strategy, research ...

Lead, Machine Learning Engineer

Newark, NJ · On-site

$107K - $141K/yr

As a Lead, Machine Learning Engineer, you will partner with Data Scientists, Data Engineers, Data Analysts and other professionals to implement machine learning models that will deliver stability ...

... MRI machines, CT Scanners, Ultrasound equipment, Echo/Vascular equipment, Nuclear Medicine ... Biomedical Engineering, Biotechnology, Bioinformatics, or related field required.5. Must exhibit a ...

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 ...

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 ...

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 ...

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 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 New Jersey are hiring for Machine Learning Biomedical Engineer jobs?

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

Senior Machine Learning (ML) Engineer

Jersey City, NJ • On-site

HealthX Ventures
Investment Clubs and Venture Capital Companies • 1 - 10 employees

$120 - $150/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 9 days ago


Job description

About Dyania Health

Dyania Health is a venture-backed company founded in 2019 which has developed Synapsis AI, an end-to-end system that combines a medically post-trained LLM with a physician-driven algorithmic reasoning engine to understand and assess clinical characteristics in electronic medical records. Synapsis AI is designed for installation within the healthcare system's computing environment or on healthcare system private clouds to automate manual chart review of EMRs, without removing any data from the healthcare system. Synapsis AI completes pre-screening on both unstructured and structured patient data, deploying medical logic with temporal sensitivity to dynamically match changing patient characteristics to complex clinical trial criteria within the exact window when a given EMR may qualify for study protocol criteria.

If you like to innovate at the forefront of technology and build software that solves important real-world problems, we'd love to hear from you! At Dyania Health we are transforming the way in which machines understand and process medical information.

About the Role

We are seeking Senior Machine Learning / Software engineers who are passionate about their craft to help us in that mission. As a senior ML engineer at Dyania, you'll design, build, and deploy scalable ML-driven systems that power biomedical information processing. In this role, you will operate at the intersection of machine learning research and production-grade software engineering, owning the full lifecycle of ML-powered microservices — from model development and evaluation to deployment, monitoring, and continuous improvement.

You will play a key technical leadership role, mentor junior engineers, and collaborate closely with product, UX, and clinical teams to translate real-world healthcare challenges into robust, scalable solutions.

Key Responsibilities
  • Design, implement, and deploy ML-powered software components within a microservice architecture.
  • Lead development and productionization of NLP and transformer-based models for biomedical information processing.
  • Own the full ML lifecycle: data preparation, model training, evaluation, optimization, deployment, and inference at scale.
  • Architect scalable and maintainable ML infrastructure and services.
  • Collaborate cross-functionally with product, UX, and clinical stakeholders to understand requirements and rapidly prototype new capabilities.
  • Analyze model and system performance; communicate findings and trade-offs clearly to technical and non-technical stakeholders.
  • Ensure reliability, scalability, and security of ML services in production environments.
  • Mentor junior engineers and contribute to raising the technical bar across the team.
  • Contribute to architectural discussions and strategic technical decisions.
  • Champion engineering best practices including testing, CI/CD, version control, and documentation.
Required Qualifications
  • 5+ years of industry experience in machine learning-focused software engineering (excluding internships and academic projects).
  • Bachelor’s or graduate degree in Computer Science, Mathematics, Electrical Engineering, or a related technical field.
  • Strong hands‑on experience training, testing, deploying, and serving ML models in production environments.
  • Experience with transformer architectures and NLP applications.
  • Experience with multi‑GPU and multi‑node distributed training and inference.
  • Proficiency in Python.
  • Proficiency in Java (and/or Kotlin/Scala) or C++.
  • Experience designing and implementing microservices.
  • Professional experience with Git and collaborative development workflows.
  • Experience with relational databases and/or NoSQL systems (e.g., knowledge graphs).
  • Strong communication skills and ability to explain technical concepts clearly.
Preferred Qualifications
  • Experience working with AWS or similar cloud platforms.
  • Experience working in agile development environments and familiarity with Jira.
  • Experience building ML systems in healthcare or other regulated environments.
  • Experience with monitoring, observability, and performance optimization in production ML systems.
What Success Looks Like
  • You deliver production‑ready ML systems that are scalable, reliable, and maintainable.
  • You proactively identify technical risks and propose thoughtful solutions.
  • You translate ambiguous biomedical problems into structured ML approaches.
  • You elevate the engineering team through mentorship and thoughtful technical leadership.
  • You effectively communicate insights and trade‑offs to diverse stakeholders.
Team Culture
  • We try every day to maintain empathy for patients and our teammates.
  • We value small egos, self‑awareness, and humility in our teammates.
  • We appreciate flexible and adaptive attitudes towards solving problems, as strategic priorities may shift.
  • We love diversity of thought, perspective, working style, skill set, knowledge, and interests amongst our team.
  • We value open dialogue and brainstorming across multidisciplinary teams.

Dyania Health is an equal opportunity employer that is committed to workplace diversity and inclusion. We do not discriminate on the basis of race, gender, gender identity, color, religion, national origin, sexual orientation, or any other legally protected characteristic as outlined by federal, state, or local laws.

  • Competitive Salary
  • Health Care Plan (Medical, Dental & Vision)
  • Retirement Plan (401k, IRA)
  • Generous Paid Time Off (Vacation, Sick & Public Holidays)
  • Family Leave (Maternity, Paternity)
  • Training & Professional Development Support
  • Remote work
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