AI/ML Developer

Stellar Science Ltd-posted 3 months ago
Albuquerque, NM
51-100 employees
Professional, Scientific, and Technical Services
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Stellar Science is a growing Albuquerque-based scientific software development company seeking talented data science artificial intelligence (AI)/machine learning (ML) software development experts who are interested in helping create, extend, and apply exciting scientific and engineering analysis applications. We develop custom software products in domains that include computer vision and image processing, image simulation, high power microwave systems modeling and simulation, laser source generation and effects modeling, computational electromagnetics (CEM), space situational awareness (SSA), high performance computing (HPC), and computer aided design (CAD) tools, among others. Our projects employ AI/ML methods and techniques such as: surrogate modeling, deep learning, classification, and generative models. A Stellar Science AI/ML Developer will help to develop novel AI/ML models and use AI/ML in your data analysis to help us gain new insights into experimental and simulation-based datasets by applying innovative processing, and visualization techniques. Your goal will be to help optimize performance, accuracy, and utility of modeling and simulation systems.

  • Develop novel AI/ML models and apply AI/ML in data analysis.
  • Gain new insights into experimental and simulation-based datasets.
  • Apply innovative processing and visualization techniques.
  • Optimize performance, accuracy, and utility of modeling and simulation systems.
  • B.S. in ML/AI related field such as computer science, data science, statistics, applied mathematics, physics, engineering.
  • Knowledge of a variety of machine learning applications (such as clustering, classification, regression) and concepts (such as graph theory, decision trees, and neural networks).
  • Experience with Python and related data science libraries (such as pandas, NumPy, SciPy, and scikit-learn).
  • Experience with C++ development for integration into statistical and/or machine learning applications beyond academic examples.
  • Experience writing programs or scripts to manipulate data and draw insights from large data sets.
  • Experience with machine learning and deep learning frameworks such as PyTorch and TensorFlow.
  • Strong experience using a variety of data mining/data analysis methods, building and implementing models, using/creating algorithms, and creating/running simulations.
  • M.S. or Ph.D. in Data Science or other quantitative, scientific, or engineering field, with substantial scientific analysis experience.
  • 2+ years of post-doctoral or industry experience as a Data Scientist or Data Analyst.
  • Experience in one or more of the following: time series analysis (such as Kalman filtering), reinforcement learning (such as Proximal Policy Optimization), instance detection (such as Mask-RCNN), robust principal component analysis, and/or physics-informed neural networks.
  • Experience working within a software production environment involving C, C++, Java, and/or TypeScript.
  • Excellent written and verbal communication skills for coordinating across teams.
  • Experience running simulation and analysis processes on scalable computing architectures including clusters, cloud-based services, or supercomputers.
  • Experience with version control (such as Git or SVN).
  • Extremely flexible work schedule.
  • Hybrid workplace model.
  • Generous benefits.
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