- At HyperSpectral we are illuminating invisible threats to protect people and the planet. HyperSpectral has created a first-of-its-kind platform that applies AI to democratize access to spectral response—the world's most reliable information source. Led by a team of problem solvers who combine decades of experience and domain expertise in AI, spectral science, and software, HyperSpectral uniquely enables real-time visibility into pathogens, contaminants, VOCs, and more, empowering companies to act before those invisible threats negatively impact their businesses and their customers.
- Cleaning and preprocessing large datasets of spectral data to ensure quality and consistency.
- Analyzing spectral data to identify patterns, anomalies, and significant features.
- Transforming raw spectral data into domain-specific outputs to enrich model performance and relevance.
- Applying appropriate spectral processing, smoothing, and enhancement techniques to find meaningful information and features.
- Designing and developing machine learning models to analyze and interpret spectral data from a variety of spectroscopic methods.
- Carrying out model optimization and parameter fine-tuning for improved accuracy and efficiency.
- Identifying and tracking appropriate evaluation metrics based on the problem domain and interpreting model performance.
- Rigorously testing and validating models against known datasets to ensure reliability and accuracy.
- Collaborating with domain experts (like chemists or physicists) to understand the context and application of spectral data.
- Communicating with other data scientists, engineers, and stakeholders to align AI/ML objectives with broader project goals.
- Staying abreast of the latest developments in AI/ML as well as spectral analysis techniques.
- Preparing reports and presentations for both technical and non-technical audiences to communicate findings and insights.
- Strong foundational knowledge in AI, machine learning, and data science.
- Proficiency in programming languages such as Python and familiarity with AI frameworks like TensorFlow or PyTorch.
- Experience with frequently used data manipulation and computational libraries, such as Pandas, Numpy, Sklearn, and Scipy.
- Good problem-solving skills with an analytical mindset.
- Ability to work collaboratively in a team environment, contributing to joint projects and initiatives.
- Experience with data processing and analysis, understanding of data structures and algorithms.
- Effective communication skills, capable of presenting technical concepts to non-technical audiences.
- Flexibility and adaptability in a fast-paced and dynamic startup environment.
- A proactive approach to learning and applying new technologies and methodologies in AI.
- Bachelor's or Master's degree in Computer Science, Computer Engineering, Data Science, a related field, or relevant work experience.
- Prior experience in AI or machine learning projects is desirable, though entry-level candidates with strong academic backgrounds may be considered.
- Ability to maintain a stationary position for extended periods, primarily sitting, to perform computer-based work.
- Manual dexterity to operate computers and other technology necessary for job functions.
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AI/ML Engineer - Remote, United States - HyperSpectral Corp
4 weeks ago
Description
Job Summary: This role of AI/ML Engineer for spectral data modeling combines expertise in machine learning with a deep understanding of spectral analysis, playing a vital role in extracting valuable insights from complex spectral datasets. This position involves a balance of technical proficiency, collaborative skills, and continuous learning to stay at the forefront of technological advancements.
Company Introduction
Responsibilities
Requirements
Education and Experience
Physical Requirements
HyperSpectral is an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements.
