Stack AV
Stack AV
Stack AV izstrādā ar mākslīgo intelektu darbināmas autonomas kravu pārvadājumu sistēmas transporta un loģistikas nozarēm. Uzņēmuma darbība apvieno mākslīgo intelektu, mašīnmācīšanos un mākoņtehnoloģijas, lai veicinātu drošākus, uzticamākus un efektīvākus kravu pārvadājumus. Izmantojot autonomo transportlīdzekļu tehnoloģijas, uzņēmums koncentrējas uz piegādes ķēžu pārvaldības, piegāžu veiktspējas un uzņēmējdarbības rezultātu uzlabošanu, savā inženiertehniskajā pieejā par prioritāti izvirzot drošību. Daudznozaru komanda darbojas loģistikas, ražošanas un ar konsultācijām saistītās jomās, attīstot viedus risinājumus mūsdienu kravu transportam.

Staff Software Engineer, ML Training Infrastructure at Stack AV (Remote, Pennsylvania)

Lead the design of scalable machine learning training infrastructure and end-to-end model pipelines. Help advance Stack AV’s autonomous trucking systems through platform engineering, performance optimization, and cross-functional collaboration.

Apraksts

  • Build and refine high-performance training platform components spanning orchestration, training abstractions, control-plane services, observability, and performance optimization.
  • Develop complete machine learning pipelines covering log processing, feature extraction, dataset schemas and storage, model configuration, training, profiling, and acceleration.
  • Evaluate training infrastructure to uncover and address performance constraints.
  • Promote system abstractions and developer tools that help machine learning engineers iterate quickly on models.
  • Adopt open-source technologies that let machine learning engineers independently profile and improve their workflows.
  • Uphold strong engineering standards and help foster a team culture centered on technical excellence.
  • Lead the architecture and implementation of a high-performance, multi-tenant AI training platform.
  • Partner with teams across ML Platform, Infrastructure, Autonomy, and Safety Evaluation.

Prasības

  • Bachelor’s or master’s degree in computer science, engineering, or a related discipline.
  • At least six years of experience developing ML platforms and machine learning applications.
  • Advanced programming ability in Python, C++, or an equivalent language.
  • Experience with Lance, PyTorch, Ray Data, or comparable technologies.
  • Demonstrated success building scalable, dependable infrastructure in a fast-moving environment and partnering with machine learning engineers across modeling teams.
  • Strong grasp of system design tradeoffs, with the communication skills to build alignment among cross-functional teams.
  • Background in model training, model optimization, or large-scale data-processing pipelines.
  • Strong analytical reasoning and problem-solving ability.
  • Clear written and verbal communication skills, including the ability to explain complex technical ideas to nontechnical stakeholders.
  • May need to verify residence, U.S. person status, and/or citizenship to meet U.S. national security and export-control requirements.

Priekšrocības

  • An equal-opportunity workplace focused on inclusion, entrepreneurship, and innovation across gender, race, age, sexual orientation, religion, disability, and identity.

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