Principal AI Scientist

Mendon, Utah, USA

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Autonomous Solutions, Inc.

Autonomous SolutionsWorldwide Leader of Industrial Vehicle AutomationExplore Our industriesMobius®Autonomous Fleet Management Systemlearn moreASI Heavy ConstructionMost Advanced Unmanned Earth-Moving Command & Controllearn moreASI...

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At ASI, we are revolutionizing industries with state-of-the-art autonomous robotics solutions. We deliver technologies that enhance safety, productivity, and efficiency. With our core values of Simplicity, Safety, Transparency, Humility, Attention to Detail and Growth guiding everything we do, we're shaping the future of automation in dynamic markets.


As a Principal AI Scientist, you will play a critical role in developing and integrating advanced AI capabilities into ASI's autonomous systems. This position focuses on designing, training, testing, and deploying machine learning models that power core autonomy features such as perception, planning, and decision-making. Working closely with Data Scientists, Simulation Specialists, and Principal Architects, you will ensure ASI's AI solutions are production-ready, reliable, and continuously improving to meet operational demands.


Responsibilities:

  • Design, develop, and train machine learning models for autonomy systems, including perception, planning, and control modules.

  • Design and implement AI-driven interfaces into the command-and-control software (e.g., Mobius), including large language model (LLM) integrations, to enable natural-language control and simplify complex vehicle configuration and command workflows.

  • Collaborate with Data Scientists to define feature requirements, understand data gaps, and improve model inputs.

  • Evaluate model performance using real-world and simulated data, refining approaches to ensure safe, robust behavior in complex environments.

  • Integrate AI models into ASI's software stack, ensuring they meet real-time, embedded, or edge-deployment requirements.

  • Partner with Simulation Specialists to test AI models in closed-loop simulations and synthetic environments.

  • Support continuous learning workflows by defining retraining strategies using operational field data.

  • Contribute to model deployment pipelines, monitoring, and lifecycle management to ensure reliability at scale.

  • Document model architectures, training procedures, evaluation results, and deployment configurations for internal knowledge sharing.


Required Qualifications:

  • Bachelor's or Master's degree in Computer Science, Electrical Engineering, Robotics, Machine Learning, or a related field.

  • 3+ years of industry experience building and deploying machine learning models in production environments.

  • Strong proficiency in Python and ML libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn).

  • Experience with real-world data preparation, feature engineering, and model evaluation.

  • Familiarity with time-series data and relational data modeling, with ability to design models that leverage both.

  • Familiarity with large language models (LLMs) and their application in building user-friendly, AI-powered control interfaces is highly desirable.

  • Solid understanding of core ML concepts, including supervised/unsupervised learning, model optimization, and validation techniques.

  • Experience deploying models to production, including on embedded systems or edge devices, is a strong plus.

  • Exposure to robotics, autonomous vehicles, sensor fusion, or control systems is highly desirable.

At Autonomous Solutions, Inc. (ASI), we are committed to fostering a diverse, inclusive, and equitable workplace where all employees and applicants have equal opportunities. We prohibit discrimination and harassment of any kind based on race, color, religion, sex, national origin, age, disability, genetic information, veteran status, sexual orientation, gender identity, or any other legally protected characteristic. ASI complies with all applicable federal, state, and local laws regarding non-discrimination in employment and is dedicated to providing reasonable accommodations for individuals with disabilities throughout the hiring process.

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Tags: Architecture Computer Science Core ML Engineering Feature engineering LLMs Machine Learning ML models Model deployment Pipelines Python PyTorch Robotics Scikit-learn TensorFlow Testing Unsupervised Learning

Perks/benefits: Career development

Region: North America
Country: United States

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