Develop, implement, and optimize LLMs and computer vision algorithms for processing and analyzing biomedical text and image data.
Design and develop software tools and pipelines for automated image analysis, data integration, and visualization, leveraging machine learning and deep learning techniques.
Collaborate with biologists and other researchers to understand their needs and translate them into technical solutions, incorporating state-of-the-art AI methodologies.
Perform data mining, statistical analysis, and machine learning on large-scale biomedical imaging datasets to extract meaningful insights and improve predictive accuracy.
Validate and benchmark AI-driven imaging algorithms and tools to ensure their accuracy, robustness, and scalability.
Document software development processes, create user manuals, and provide training and support to end-users, particularly focusing on AI applications.
Stay up-to-date with the latest advancements in AI, computer vision, biomedical imaging, computational biology, and data science, and apply this knowledge to improve existing tools and methodologies.
Participate in interdisciplinary team meetings, present findings, and contribute to scientific publications and grant proposals, emphasizing AI and computer vision innovations.
Identify and implement new AI technologies and frameworks to enhance the capabilities of biomedical imaging tools and methodologies.

Ph.D. or Master’s degree in Data Science, Computer Science, Biomedical Engineering, Bioinformatics, or a related field.
Proven experience in biomedical imaging analysis, AI, and computer vision, preferably in HTS and HCS contexts.
Strong programming skills in languages such as Python.
Well versed with AI and machine learning frameworks and libraries such as TensorFlow, PyTorch, PydanticAI, and LLM observability.
Experience with image analysis software and libraries such as ImageJ, CellProfiler, OpenCV, or similar.
Knowledge of statistical analysis and data visualization techniques.
Familiarity with high-performance computing and cloud-based data processing environments.
Excellent problem-solving skills and the ability to work both independently and as part of a team.
Strong communication skills and the ability to convey complex technical concepts to non-technical audiences.
Experience in developing AI-driven software tools for biomedical research.
Experience with version control systems such as Git.
Experience with workflow automation tools.
Previous experience working in a collaborative, interdisciplinary research environment.

A background in biology and/or medicine.
Knowledge of code packaging, containerization technologies, and continuous integration pipelines.
DevOps experience with Kubernetes and workflow automation.

This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location. #IND
Do you have the legal authorization to work on a full-time, indefinite basis in the country where this role is located?
Can you perform the essential functions of this job without reasonable accommodation?
Are you willing and able to work at the specified job location, or are you open to relocation if required?
Does accepting employment with Axle or performing the duties required for this role conflict with any non-compete, non-solicitation, or other contractual agreements you may have?
Do you meet the eligibility requirements for obtaining a US Government Security Clearance?
Do you now, or will you in the future, require sponsorship for employment authorization in the United States?

Axle is hiring a Data Scientist II

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