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Biomedical Ai Jobs (NOW HIRING)

Natera

OR

$232K - $243K/yr

... biomedical AI agents, AI-driven analysis platforms, forecasting algorithms. * Identify high-value use cases across drug development (e.g., trial design, patient selection, translational insights ...

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How much do biomedical ai jobs pay per hour?

As of Jul 21, 2026, the average hourly pay for biomedical ai in the United States is $28.53, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $32.21 per hour, depending on experience, location, and employer.

What are some typical challenges faced by professionals working in Biomedical AI, and how can applicants prepare to address them?

Professionals in Biomedical AI often encounter challenges such as integrating diverse data types (e.g., imaging, genomics, clinical records), ensuring data privacy and compliance with healthcare regulations, and translating AI models into clinically actionable insights. To prepare, applicants should familiarize themselves with healthcare data standards, develop strong interdisciplinary communication skills, and stay updated on ethical considerations in medical AI. Experience working with real-world biomedical datasets and collaborating with clinicians or researchers will also be highly valuable.

What are the key skills and qualifications needed to thrive as a Biomedical AI Specialist, and why are they important?

To thrive as a Biomedical AI Specialist, you need a solid background in biomedical sciences, computer science, and machine learning, often supported by an advanced degree (e.g., MS or PhD) in a related field. Familiarity with programming languages like Python or R, experience with AI frameworks (such as TensorFlow or PyTorch), and knowledge of healthcare data systems are essential. Strong analytical thinking, problem-solving abilities, and the capacity to communicate complex technical concepts to interdisciplinary teams are vital soft skills. These competencies enable the effective development and deployment of AI solutions that address critical challenges in biomedical research and healthcare delivery.

Can AI replace biomedical scientists?

Biomedical AI professionals develop and apply artificial intelligence tools to analyze biological data, assist in diagnostics, and support research. While AI can automate certain tasks and enhance data analysis, it is unlikely to fully replace biomedical scientists, who provide critical expertise, interpretation, and decision-making in complex biological and medical contexts.

What is Biomedical AI?

Biomedical AI refers to the application of artificial intelligence technologies in the field of biomedical research and healthcare. This includes using machine learning, deep learning, and data analytics to analyze complex biological data, improve diagnostics, personalize treatment, and accelerate drug discovery. Biomedical AI professionals work at the intersection of computer science, biology, and medicine, developing tools that can help interpret medical images, predict disease outcomes, and uncover new insights from large-scale health data. The field is rapidly growing and is seen as a key driver in the future of healthcare innovation.

What is the role of AI in biomedical science?

In biomedical AI roles, AI is used to analyze large datasets, develop predictive models, and assist in drug discovery and personalized medicine. Professionals in this field often work with machine learning algorithms, bioinformatics tools, and require knowledge of biology and data science to improve healthcare outcomes.

What to do to become a biomedical AI specialist?

To become a biomedical AI specialist, you should obtain a strong foundation in computer science, machine learning, and biomedical sciences through relevant degrees such as computer science, bioinformatics, or biomedical engineering. Gaining experience with programming languages like Python, working with healthcare data, and understanding AI tools and frameworks are essential. Certifications in AI or data science and familiarity with medical datasets can also enhance your qualifications.

What is the difference between Biomedical Ai vs Biomedical Data Scientist?

AspectBiomedical AiBiomedical Data Scientist
Required CredentialsDegree in AI, Machine Learning, or related fields; knowledge of biology and healthcareDegree in Data Science, Statistics, or related; strong biology background
Work EnvironmentResearch labs, healthcare tech companies, biotech firmsHospitals, research institutions, biotech companies
Employer & Industry UsageDevelops AI models for medical diagnosis, drug discovery, personalized medicineAnalyzes biomedical data to extract insights, support clinical decisions

Biomedical Ai focuses on developing AI algorithms for healthcare applications, combining AI expertise with biomedical knowledge. Biomedical Data Scientists analyze biomedical data to generate insights and support research. While both roles require a strong understanding of biology and data skills, Biomedical Ai emphasizes AI model development, whereas Biomedical Data Scientists focus on data analysis and interpretation.

What is the salary of a biomedical AI scientist?

The salary of a biomedical AI scientist typically ranges from $80,000 to $150,000 annually, depending on experience, education, location, and the complexity of projects. Professionals with advanced degrees and skills in machine learning, data analysis, and biomedical sciences tend to earn higher salaries.
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Biomedical Ai jobs near you
Infographic showing various Biomedical Ai job openings in the United States as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $59,333 per year, or $28.5 per hour.

BioMedical AI Research Engineer

Xaira Therapeutics

South San Francisco, CA

$190K - $280K/yr

Other

Re-posted 18 days ago

Job description

About the Role
We are seeking a Biomedical AI Engineer to design and deploy agentic AI systems that can reason over biomedical knowledge, plan multi-step analyses, and autonomously integrate diverse scientific data sources to accelerate therapeutic discovery.

This role goes beyond traditional LLM + RAG pipelines. You will build AI agents that can retrieve, synthesize, evaluate, and act on biomedical information across literature, omics datasets, and clinical records operating as intelligent systems embedded within discovery workflows.

Key Responsibilities

  • Design and implement agentic AI architectures capable of multi-step reasoning, planning, and tool use in biomedical contexts.
  • Develop LLM-based agents that dynamically retrieve, rank, and synthesize knowledge from scientific literature, knowledge graphs, omics datasets, and clinical data.
  • Build memory and feedback mechanisms that allow agents to refine hypotheses, update context, and adapt to evolving data.
  • Integrate external tools (analysis pipelines, simulation engines, statistical models, databases) into autonomous agent workflows.
  • Architect scalable systems that combine structured and unstructured biomedical data within production-grade AI environments.
  • Collaborate closely with computational biologists, translational scientists, and software engineers to embed agentic systems into real-world discovery pipelines.
  • Evaluate robustness, reliability, and interpretability of autonomous systems in high-stakes biomedical settings.

Qualifications

  • Degree in Computer Science, Machine Learning, Computational Biology, Biomedical Informatics, or related field.
  • Strong hands-on experience with large language models, including fine-tuning, alignment, and structured prompting.
  • Experience building agent-based systems or complex LLM orchestration frameworks (e.g., multi-agent systems, tool-using LLMs, planning modules).
  • Proficiency in Python and modern ML frameworks (PyTorch, JAX, TensorFlow).
  • Experience working with large-scale biomedical datasets (genomics, transcriptomics, clinical records, or scientific corpora).

Preferred

  • Experience designing autonomous research assistants or AI systems that perform multi-step scientific reasoning.
  • Familiarity with knowledge graphs, hybrid symbolic-neural systems, or multimodal foundation models.
  • Understanding of privacy, security, and regulatory considerations in healthcare AI.

Compensation

We offer a competitive compensation and benefits package, seeking to provide an open, flexible, and friendly work environment to empower employees and provide them with a platform to develop their long-term careers. A Summary of Benefits is available for all applicants. We offer a competitive package that includes base salary, bonus, and equity. The base pay range for this position is expected to be $190,000 - $280,000 annually; however, the base pay offered may vary depending on the market, job-related knowledge, skills and capabilities, and experience.
Xaira Therapeutics an equal-opportunity employer. We believe that our strength is in our differences. Our goal to build a diverse and inclusive team began on day one, and it will never end.

TO ALL RECRUITMENT AGENCIES: Xaira Therapeutics does not accept agency resumes. Please do not forward resumes to our jobs alias or employees. Xaira Therapeutics is not responsible for any fees related to unsolicited resumes.

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