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Biomedical Machine Learning Jobs in New York (NOW HIRING)

... processing, machine learning, and capability in applying various mathematical algorithms for biomedical engineering applications, and prepared for conducting human subject research including ...

... biomedical engineering, applied mathematics, or a related technical field; or a bachelors degree with at least one year of relevant work experience Strong foundation in machine learning, statistics ...

... biomedical engineering, applied mathematics, or a related technical field; or a bachelors degree with at least one year of relevant work experience Strong foundation in machine learning, statistics ...

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Biomedical Machine Learning information

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How much do biomedical machine learning jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for biomedical machine learning in New York is $31.21, according to ZipRecruiter salary data. Most workers in this role earn between $26.54 and $35.24 per hour, depending on experience, location, and employer.

What is a biomedical machine learning?

A Biomedical Machine Learning job involves developing and applying machine learning algorithms to analyze biomedical data for healthcare and research applications. Professionals in this field work with medical imaging, genomics, electronic health records, and wearable device data to improve disease diagnosis, treatment, and patient outcomes. They collaborate with researchers, clinicians, and data scientists to design predictive models and extract insights from complex biological data. This role requires expertise in machine learning, data processing, and domain-specific knowledge in healthcare or life sciences.

What does a biomedical machine learning do?

A typical day in Biomedical Machine Learning involves cleaning and preparing biomedical datasets, developing or refining machine learning models, running experiments, and interpreting results in collaboration with domain experts such as bioinformaticians and clinicians. Professionals often participate in team meetings to discuss project goals, share insights, and adjust research directions based on feedback. The role may also involve reading scientific literature to stay current with new methodologies and contributing to academic publications or technical documentation. Working closely with both technical and healthcare-focused colleagues, you'll help translate data-driven insights into meaningful biomedical solutions that impact patient care or research outcomes.

What are the key skills and qualifications needed to thrive in biomedical machine learning, and why are they important?

To thrive in Biomedical Machine Learning, you need a solid background in statistics, machine learning, programming (Python or R), and a strong understanding of biological or medical data, often supported by advanced degrees in computer science, biomedical engineering, or related fields. Experience with frameworks like TensorFlow, PyTorch, and familiarity with biomedical datasets is highly valued, and certifications in data science or biomedical informatics can be advantageous. Strong analytical thinking, communication skills, and the ability to collaborate with interdisciplinary teams are crucial soft skills. These competencies are vital to developing robust models that address complex healthcare challenges while ensuring scientific rigor and regulatory compliance.

Infographic showing various Biomedical Machine Learning job openings in New York as of August 2026, with employment types broken down into 1% As Needed, 79% Full Time, 19% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $64,912 per year, or $31.2 per hour.

Senior Machine Learning (ML) Engineer

HealthX Ventures

Jersey City, NJ • On-site

$120 - $150/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 19 days ago


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.


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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