Algorithm Engineer, Deep Learning & Vision (New Grad)

Job description

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<h3><strong>Company Introduction</strong></h3>
<p>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.</p>
<h3><strong>Key Responsibilities</strong></h3>
<ul>
<li><strong>Model Implementation & Iteration:</strong> Participate in the development, training, and optimization of state-of-the-art deep learning models for autonomous driving, with a focus on end-to-end architectures, including perception, online mapping, and end-to-end planning.</li>
<li><strong>Full Lifecycle Execution:</strong> Engage in the entire machine learning workflow under the guidance of domain experts, spanning from data curation and data analysis to model experimentation, hyperparameter tuning, and rigorous performance metric verification.</li>
<li><strong>Cross-Functional Collaboration:</strong> Partner with simulation, infrastructure, and downstream planning/control teams to deploy, evaluate, and integrate machine learning components into our production pipeline for autonomous trucks.</li>
<li><strong>Literature Tracking:</strong> Stay abreast of the latest research breakthroughs in computer vision and generative AI, and actively bench-test promising SOTA methods to solve real-world corner cases.</li>
</ul>
<h3><strong>How You'll Grow</strong></h3>
<p>This matters as much to us as what you'll ship.</p>
<ul>
<li><strong>You get a real mentor.</strong> Every engineer is paired with senior-level engineers developing you. Mentorship here is weighted toward design and judgment: how to frame a problem, what to build and why, how to tell whether a solution is actually right.</li>
<li><strong>We promote fast.</strong> Managers are expected to push engineers to attempt work above their current level, and to promote in the next cycle when they deliver it.</li>
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<h3><strong>Qualifications</strong></h3>
<h3>Required<strong>:</strong></h3>
<ul>
<li><strong>Education:</strong> A Bachelor's, Master's, or Ph.D. (including upcoming graduates) in Computer Science, Robotics, Electrical Engineering, Applied Mathematics, Physics, or a related quantitative field.</li>
<li><strong>You have trained neural networks.</strong> Coursework, research, personal projects, open-source work, and internships all count. We care that you have actually run the loop: built a model, trained it, found out why it was not working, and fixed it.</li>
<li><strong>Core Knowledge:</strong> Strong theoretical foundation in machine learning and deep learning, with a solid understanding of modern architectures (e.g., Transformers, CNNs, Graphs).</li>
<li><strong>Technical Stack:</strong> Proficiency in Python and deep learning frameworks such as PyTorch, along with strong software engineering fundamentals (data structures, algorithms, and clean coding practices).</li>
<li><strong>Attributes:</strong> High self-motivation, strong analytical and problem-solving skills, a fast learner in a high-velocity startup environment, and a strong team-player mindset.</li>
</ul>
<h3>Preferred<strong>:</strong></h3>
<ul>
<li><strong>Computer vision.</strong> Research or projects in computer vision, and particularly in 3D.</li>
<li><strong>Specific Research Directions:</strong> Academic thesis or deeply focused research experience in one or more of the following domains:</li>
<ul>
<li>Computer Vision (2D or 3D)</li>
<li>Online Mapping, Vectorization, or Visual SLAM</li>
<li>Prediction and Behavioral Modeling</li>
</ul>
<li><strong>Academic Achievements:</strong> A track record of research publications in machine learning, computer vision, or robotics conferences/journals (e.g., CVPR, ICCV, ECCV, NeurIPS, ICLR, ICRA, IROS).</li>
<li><strong>Engineering Plus:</strong> Hands-on experience with model deployment, quantization, distillation, or inference acceleration tools (e.g., TensorRT, ONNX, CUDA, C++).</li>
<li><strong>Industry Exposure:</strong> Prior internship experience within the autonomous driving industry or advanced robotics labs.</li>
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