Applied Intuition
Senior Software Engineer - ML Infrastructure
Applied Intuition, Mountain View, California, us, 94039
About Applied Intuition
Applied Intuition is a Tier 1 vehicle software supplier that accelerates the adoption of safe and intelligent machines worldwide. Founded in 2017, Applied Intuition delivers the definitive ADAS/AD toolchain and a world-class vehicle platform to help customers shorten time to market, build industry-leading products, and create next-generation consumer experiences. 18 of the top 20 global automakers trust Applied Intuition’s solutions to drive the production of modern vehicles. Applied Intuition serves the automotive, trucking, construction, mining, agriculture, and defense industries and is headquartered in Mountain View, CA, with offices in Ann Arbor and Detroit, MI, Washington, D.C., Munich, Stockholm, Seoul, and Tokyo. Learn more at
https://appliedintuition.com .Please note that we are an in-office company, which means the expectation is that you would come in to your Applied Intuition office 5 days a week.About the role
We are looking for both infrastructure engineers with expertise in machine learning pipelines and ML engineers that want to work beyond modeling to join the Data & ML infra group. This role will work across the entire ML lifecycle (dataset generation, training frameworks, compute, evaluation, and deployment) and work directly with modeling teams. This team is a good fit if you are excited to work on broad, ambiguous problems and develop across the entire ML stack. At Applied Intuition, we encourage all engineers to take ownership over technical and product decisions, closely interact with external and internal users to collect feedback, and contribute to a thoughtful, dynamic team culture.At Applied Intuition, you will:
Design and implement distributed cloud GPU training approaches for deep learning model training and evaluationBuild end-to-end machine learning pipelines and integrate them into core product workflowsEncourage change, especially in support of ML engineering best practices, and maintain a high standard of excellenceCollaborate with engineers across the entire company to solve complex data problems at scaleWe're looking for someone who has:
Experience with building software components to address production, full-stack machine learning challenges. This is not purely a research problemOpinions about building a company-wide platform for ML training, evaluation, and deploymentKnowledge of the open source landscape with judgment on when to choose open source versus build in-houseExcellent analytical and problem-solving skillsNice to have:
Experience working with cloud data processing technologies (Apache Spark, ElasticSearch, Presto, SQL, etc.)Experience with developing, running, and managing orchestration systems like Airflow and Flyte that non engineers can use to build data pipelines.Experience with ML modeling frameworks (PyTorch, Tensorflow, etc.), and model serving platforms (TorchServe, TensorFlow Serving, NVIDIA Triton inference server, etc.)The salary range for this position is $ 153,000 - $222,000
USD annually. This salary range is an estimate, and the actual salary may vary based on the Company's compensation practices.
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Applied Intuition is a Tier 1 vehicle software supplier that accelerates the adoption of safe and intelligent machines worldwide. Founded in 2017, Applied Intuition delivers the definitive ADAS/AD toolchain and a world-class vehicle platform to help customers shorten time to market, build industry-leading products, and create next-generation consumer experiences. 18 of the top 20 global automakers trust Applied Intuition’s solutions to drive the production of modern vehicles. Applied Intuition serves the automotive, trucking, construction, mining, agriculture, and defense industries and is headquartered in Mountain View, CA, with offices in Ann Arbor and Detroit, MI, Washington, D.C., Munich, Stockholm, Seoul, and Tokyo. Learn more at
https://appliedintuition.com .Please note that we are an in-office company, which means the expectation is that you would come in to your Applied Intuition office 5 days a week.About the role
We are looking for both infrastructure engineers with expertise in machine learning pipelines and ML engineers that want to work beyond modeling to join the Data & ML infra group. This role will work across the entire ML lifecycle (dataset generation, training frameworks, compute, evaluation, and deployment) and work directly with modeling teams. This team is a good fit if you are excited to work on broad, ambiguous problems and develop across the entire ML stack. At Applied Intuition, we encourage all engineers to take ownership over technical and product decisions, closely interact with external and internal users to collect feedback, and contribute to a thoughtful, dynamic team culture.At Applied Intuition, you will:
Design and implement distributed cloud GPU training approaches for deep learning model training and evaluationBuild end-to-end machine learning pipelines and integrate them into core product workflowsEncourage change, especially in support of ML engineering best practices, and maintain a high standard of excellenceCollaborate with engineers across the entire company to solve complex data problems at scaleWe're looking for someone who has:
Experience with building software components to address production, full-stack machine learning challenges. This is not purely a research problemOpinions about building a company-wide platform for ML training, evaluation, and deploymentKnowledge of the open source landscape with judgment on when to choose open source versus build in-houseExcellent analytical and problem-solving skillsNice to have:
Experience working with cloud data processing technologies (Apache Spark, ElasticSearch, Presto, SQL, etc.)Experience with developing, running, and managing orchestration systems like Airflow and Flyte that non engineers can use to build data pipelines.Experience with ML modeling frameworks (PyTorch, Tensorflow, etc.), and model serving platforms (TorchServe, TensorFlow Serving, NVIDIA Triton inference server, etc.)The salary range for this position is $ 153,000 - $222,000
USD annually. This salary range is an estimate, and the actual salary may vary based on the Company's compensation practices.
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