
Bot Auto offers autonomous trucking as a service to freight customers. It uses L4 autonomous trucks and an AI-driven fleet-operations platform to run vehicles without human drivers. The companyβ¦

Bot Auto offers autonomous trucking as a service to freight customers. It uses L4 autonomous trucks and an AI-driven fleet-operations platform to run vehicles without human drivers. The companyβ¦
What they do: Operate L4 autonomous truck fleet and offer Transportation-as-a-Service (TaaS) to shippers and 3PLs
Founded: 2023
Headquarters: Houston, Texas
Notable customers: J.B. Hunt; Ryan Transportation; Steves & Sons
Recent disclosed funding: $20M Pre-A / pre-Series A
Autonomous trucking and freight transportation
2023
Freight and Package Transportation
$20,000,000
Reported oversubscribed Pre-A round to accelerate R&D and scale operations
20000000
Dealroom/other profiles list a $20M round in 2024/2026 reporting; some sources present overlapping round dates
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Company Introduction
At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a start-up and the wisdom of seasoned experts, Bot Auto boasts a team that has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create miracles and propel the future of transportation. Join us and transform your dreams into reality.
We are seeking a highly skilled and motivated Software Engineer to design, develop, and scale our machine learning annotation, evaluation, and training infrastructure. This role is central to the quality and velocity of our perception and ML models β from curating and managing high-quality annotated datasets, to building robust evaluation pipelines that drive continuous model improvement. The ideal candidate combines strong systems engineering skills with a deep understanding of ML Workflows/Ops and large-scale data infrastructure.
Key Responsibilities
Machine Learning & Deep Learning Infrastructure
Data Infrastructure
Qualifications Required :
Preferred
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Educational Background: Bachelor's or Master's in Computer Science, or equivalent practical experience.
Strong Programming Skills: Strong proficiency in Python; working knowledge of C++
ML/DL Infrastructure Experience β Demonstrated hands-on experience building or scaling at least one of the following in a production environment:
Evaluation platforms β automated model benchmarking, metric computation, and regression tracking across model versions.
Training infrastructure β distributed training pipelines, experiment tracking, and model lifecycle management (e.g. W&B, MLflow, ClearML).
Dataset curation & feature stores β versioned dataset management, data lineage, and tooling for high-quality training data at scale.
Annotation platforms β tooling or pipelines that support high-throughput, high-accuracy labeling workflows.
Distributed Systems β Strong experience with distributed computing and container orchestration β Kubernetes, Spark, or comparable frameworks.
Ability to operate independently: scope ambiguous problems, make sound architecture decisions, and drive them to completion.