Scientific Software Engineer - AI/ML for Hyperspectral Imaging

LBL • $104K — $116K *
Berkeley, CA 94704In-Person
Technical Services
Less than 5 years of experience
6 days ago
Job Overview by Ladders

Qualifications

  • Bachelor's degree and 2+ years of related experience, or advanced degree (Master's/PhD) without experience.
  • Experience with Python-based scientific libraries (e.g., NumPy, PyTorch, TensorFlow).
  • Hands-on experience with complex scientific datasets (e.g., imaging, multimodal data).
  • Proven experience in developing and applying AI/ML models for scientific analysis.
  • Experience in collaborative or open-source software development.
  • Ability to design and maintain data analysis pipelines or workflows.
  • Proficiency in validating results against technical and scientific expectations.

Responsibilities

  • Expand AI-driven segmentation and feature extraction across scientific modalities.
  • Develop specialized ML models for hyperspectral imaging data.
  • Create interfaces integrating ML models into automation systems.
  • Implement scalable data processing pipelines for structured scientific data.
  • Ensure reproducibility and interoperability of software workflows.
  • Collaborate with scientists to translate needs into software solutions.
  • Contribute to open-source projects and provide user documentation and support.

Benefits

  • Full-time, term position with potential for extension or conversion to career appointment.
  • Flexible hybrid work schedule eligible.
  • Located at Lawrence Berkeley National Laboratory, a hub for scientific research and technology.
Full Job Description
Lawrence Berkeley National Laboratory's (Berkeley Lab) Advanced Light Source (ALS) Division has an opening for a Scientific Software Engineer specializing in AI/ML for hyperspectral imaging. This role advances AI-driven scientific discovery by developing machine learning methods and scalable data analysis tools for complex, high-dimensional scientific datasets.

The engineer will build and generalize segmentation, feature extraction, and modeling workflows, including development of a foundation model to extract scientific information from hyperspectral imaging data across infrared imaging, resonant soft X-ray scattering, tomography, and ptychography.

Key responsibilities:
  • Expand and generalize AI-driven segmentation and feature extraction workflows across multiple scientific modalities and domains.
  • With general guidance, develop and apply specialized machine learning models for hyperspectral imaging data, serving as a key target domain for high-dimensional spectral-spatial analysis.
  • Operating under broad direction, develop interfaces and data products that enable machine learning models to be integrated into higher-level automation and agent-based systems.
  • Implement scalable pipelines that transform experimental data into structured, semantically meaningful scientific representations.
  • Ensure reproducibility, traceability, and interoperability of software and AI workflows across systems and facilities.
  • Collaborate with scientists and engineers to gather requirements, validate results, and translate scientific needs into software solutions.
  • Design, test, deploy, and maintain robust software using modern development practices (e.g., CI/CD, version control, unit testing).
  • Contribute to open-source projects, develop documentation, provide user support, and communicate work through presentations.


Required qualifications:
  • Bachelor's degree and a minimum of 2 years of related experience; or an advanced degree without experience (Master's or PhD); or equivalent years of work experience.
  • Experience with the open-source scientific Python ecosystem (e.g., NumPy, PyTorch, TensorFlow, scikit-learn).
  • Hands-on experience analyzing complex scientific datasets, including imaging, multivariate, multimodal, multichannel, or volumetric data.
  • Hands-on experience developing, training, or applying AI/ML models, including segmentation methods, for scientific data analysis.
  • Experience developing or contributing to software projects, including collaborative or open-source development.
  • Experience building or maintaining data analysis pipelines or scientific workflows.
  • Ability to work collaboratively with a team of scientists and engineers.
  • Knowledge of AI/ML principles and data analysis methods relevant to complex scientific data, including segmentation, feature extraction, model training, validation, and interpretation.
  • Knowledge of GPU acceleration and performance profiling for large scale workflows
  • Demonstrated ability to design and evaluate workflows for processing, analyzing, and representing complex scientific imaging and high-dimensional data.
  • Proficiency to validate data quality, model outputs, and workflow results against technical and scientific expectations.
  • Proven capability to develop, test, debug, document, and maintain reproducible software and machine learning workflows.
  • Effectiveness in communicating technical results clearly, both in writing and verbally, to interdisciplinary audiences.
  • Flexibility and capacity to learn new scientific domains, data modalities, tools, and computational techniques within evolving project timelines.


Desired skills/knowledge:
  • Experience with hyperspectral scientific datasets.
  • Experience with High-Performance Computing (HPC) environments.
  • Experience with MLOps tools such as MLflow.
  • Experience with CI/CD tools (e.g., GitHub Actions).
  • Familiarity with hyperspectral imaging data.
  • Familiarity with agent-based or AI orchestration frameworks (e.g., LLM-based or multi-agent systems).


Additional information:
  • Application date: Priority consideration will be given to candidates who apply by June 16, 2026. Applications will be accepted until the job posting is removed.
  • Appointment type: This is a full-time 2 year, term appointment with the possibility of extension or conversion to Career appointment based upon satisfactory job performance, continuing availability of funds and ongoing operational needs.
  • Salary range: The expected salary for this position is $104,580 - $116,184, which depends upon the candidate's skills, knowledge, and abilities. This includes education, certifications, and years of experience.
  • Background check: This position is subject to a background check. Any convictions will be evaluated to determine if they directly relate to the responsibilities and requirements of the position. Having a conviction history will not automatically disqualify an applicant from being considered for employment.
  • Work modality: This position is eligible for a hybrid work schedule - a combination of teleworking and performing work on site at Lawrence Berkeley National Lab, 1 Cyclotron Road, Berkeley, CA. Individuals working a hybrid schedule must reside within 150 miles of Berkeley Lab.


Want to learn more about working at Berkeley Lab? Please visit: careers.lbl.gov

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