Machine Learning Engineer
Remote /
Technology Team /
Full-Time
/ Remote
Machine Learning Engineer
Company IntroductionAt HyperSpectral, we are revolutionizing the way spectral data is unlocked through cutting edge AI/ML technologies, enabling the rapid detection of bacteria, viruses, contaminants and other hazardous substances with unprecedented speed and accuracy. Our innovative solutions are transforming industries, providing critical decision support orders of magnitude faster than existing alternatives. As a rapidly expanding company, our exceptional co-founder team brings together top scientific, technological, and management expertise, boasting decades of success in driving technologies from concept to implementation. We are seeking driven, talented individuals to join our ambitious journey and contribute to shaping the future of spectral data analysis. Machine Learning Engineer Responsibilities:We are looking for a Machine Learning (ML) Engineer to help us extract value from our data. You will lead all the processes from data collection, cleaning, and preprocessing, to training models and deploying them to production.
The ideal candidate will be passionate about artificial intelligence and stay up-to-date with the latest developments in the field.
Machine Learning Engineer Requirements:Understanding business objectives and developing models that help to achieve them, along with metrics to track their progressExperience with machine learning and computer vision modelsManaging available resources such as data, and softwareAnalyzing the ML algorithms that could be used to solve a given problem and ranking them by their success probabilityDetail-oriented forward thinker to help make HyperSpectral’s vision into realityAbility to influence cross-functionally without direct authorityStrong business acumen and application of company prioritiesExperience in making data driven decisionsExcellent written, verbal, and technical communicatorAble to manage work to meet deadlinesDemonstrated ability to take a project from ideation through to implementationUnderstanding of big data, data analytics, artificial intelligence and machine learning is keyAbility to operate in a fast-paced startup environment and adapt to changing business needs
Skills:Proficiency with a deep learning framework such as TensorFlow or KerasProficiency with Python and basic libraries for machine learning such as scikit-learn, pandas, and numpyExpertise in visualizing and manipulating big datasetsAbility to select hardware to run an ML model with the required latencyAWS/ML Ops experienceExploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real worldVerifying data quality, and/or ensuring it via data cleaningSupervising the data acquisition process if more data is neededFinding available datasets online that could be used for trainingDefining validation strategiesDefining the preprocessing or feature engineering to be done on a given datasetDefining data augmentation pipelinesTraining models and tuning their hyperparametersAnalyzing the errors of the model and designing strategies to overcome themDeploying models to productionDevelop tests to verify and validate conclusions
Salary : Competitive and commensurate with experienceLocation: HyperSpectral staff is remote. However, the company's key personnel are located in the Washington, DC; Cambridge, MA, Austin, TX and Los Angeles, CA areas. Contact: LeverHyperSpectral 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.
Requirements
Skills
Salary : Competitive and commensurate with experience
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.
