HyperSpectral
AI/ML Engineer
đź“Ť
United States
🧪
Not Applicable
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
Salary : Competitive and commensurate with experience
Location: HyperSpectral staff is remote. However, the company's key personnel are located in the Washington, DC; Cambridge, MA; Atlanta, GA; Austin, TX and Los Angeles, CA areas.
Company Introduction
- 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
Salary : Competitive and commensurate with experience
Location: HyperSpectral staff is remote. However, the company's key personnel are located in the Washington, DC; Cambridge, MA; Atlanta, GA; Austin, TX and Los Angeles, CA areas.