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Founding ML Engineer

At Coco, our mission is to revolutionize urban logistics by empowering cities, boosting local economies, and delivering delightful customer experiences. We connect people with local merchants through our fleet of on-demand delivery robots, helping merchants reach their customers faster and more efficiently. By building innovative robotic systems that seamlessly navigate city sidewalks, Coco plays a key role in reshaping the future of last-mile delivery and enhancing local businesses.

To deliver on our mission, we are building an autonomy team to develop the AI technology that will enable our robot pilots to scale efficiently, sustainably, and safely. This involves building an autonomy stack ground-up based on our millions of miles of last-mile delivery routes, proprietary video streams, and LiDAR data.

What is the scope of this role?

As a Founding Machine Learning Engineer, you will be responsible for standing up Coco’s autonomy stack alongside the CTO and fellow team members in the autonomy team. You will be responsible for designing, developing, and deploying our machine learning models as part of an end-to-end stack that feeds off millions of miles of daily piloted deliveries and sensor data (camera, LiDAR, etc.). The impact of this will be massive improvements to our robot-to-pilot ratio thereby allowing every person living in an urban area to benefit from last-mile delivery. In this role, you must accomplish the following:

  • Develop the architecture and implementation of machine learning models that power the autonomous vehicle’s perception, decision-making, and control systems.

  • Design and implement algorithms for object detection, sensor fusion, path planning, and real-time decision-making.

  • Develop and maintain robust data pipelines to ingest, label, and preprocess data from multiple sensors (LiDAR, cameras, radar).

  • Train and optimize deep learning models using simulation and real-world data. Focus on improving system accuracy, robustness, and efficiency.

  • Build simulation environments to test various driving scenarios and edge cases; work closely with the hardware team to ensure smooth integration of software with vehicle systems.

  • Ensure that the autopilot system adheres to safety standards and regulations, incorporating redundancy and fail-safe mechanisms.

  • Play a key role in recruiting, mentoring, and leading a high-performance machine learning and autonomy team.

Must have competencies:

  • 2+ years experience in machine learning, computer vision, robotics, or autonomous systems.

  • Proven track record of training and deploying a real world neural network.

  • Extremely well versed in the models and techniques that have been used and are currently in use with autonomous driving or robotics systems in constrained, production environments. SfM, SLAM, large-scale mapping & localization, RL, imitation learning, neural rendering, etc.

  • Expertise in training and deploying deep learning models, particularly in vision (CNNs, object detection, semantic segmentation).

  • Excellent programming skills in Python and C++. Practical experience with PyTorch.

  • Experience in optimizing large-scale ML models and deploying them on distributed cloud/edge infrastructure.

  • Strong leadership and communication skills.

Nice to have:

  • Contributions to open-source autonomous vehicle frameworks (e.g., Autoware, Apollo).

  • Experience with hardware integration and low-level system programming (ROS, CAN bus).

  • Familiarity with reinforcement learning and imitation learning for decision-making in autonomous systems.

  • Familiarity with regulatory and safety standards for autonomous vehicles (ISO 26262, UL 4600).

Average salary estimate

$135000 / YEARLY (est.)
min
max
$120000K
$150000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Founding ML Engineer, Coco

At Coco, we’re on a mission to revolutionize urban logistics in San Francisco, and we’re looking for a Founding Machine Learning Engineer to join our dynamic team! Picture this: a world where delivery robots seamlessly navigate city sidewalks, helping local merchants connect with their customers faster. As a Founding ML Engineer, you’ll play a critical role in shaping Coco’s autonomy stack, working side-by-side with our CTO and an enthusiastic autonomy team. This isn't just about sitting in front of a screen; you’ll be designing, developing, and deploying machine learning models that enhance our robot delivery systems using millions of daily piloted deliveries and sensor data—think cameras and LiDAR! Imagine getting to implement algorithms for object detection and real-time decision-making while ensuring that our autopilot systems adhere to safety standards. Plus, you’ll help foster a high-performance ML and autonomy team, mentoring the next generation of innovators. With over two years of experience in machine learning or robotics, if you're passionate about contributing to local economies and empowering urban life, then Coco is the place for you! Your work here means making a massive impact on last-mile delivery, and you'll be at the forefront of tech innovation in the exciting realm of autonomous vehicles.

Frequently Asked Questions (FAQs) for Founding ML Engineer Role at Coco
What are the responsibilities of a Founding Machine Learning Engineer at Coco?

As a Founding Machine Learning Engineer at Coco, your responsibilities will include designing and implementing machine learning models that power autonomy systems, developing algorithms for object detection and sensor fusion, and building robust data pipelines. You’ll also train deep learning models and create simulations for testing various driving scenarios. Your role is crucial in enhancing the efficiency and safety of our delivery robots.

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What qualifications do I need to become a Founding Machine Learning Engineer at Coco?

To qualify for the Founding Machine Learning Engineer position at Coco, you should have 2+ years of experience in machine learning, computer vision, or autonomy systems. You need a proven track record in training and deploying neural networks, with expertise in deep learning models such as CNNs. Strong programming skills in Python and C++ are essential, along with experience in optimizing large-scale models.

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What skills are essential for a Founding ML Engineer role at Coco?

Essential skills for the Founding Machine Learning Engineer role at Coco include expertise in training deep learning models, excellent programming skills in Python and C++, and familiarity with algorithms for object detection and path planning. Leadership and communication skills are also crucial, as you'll be mentoring team members and collaborating closely with hardware teams.

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How does the role of Founding ML Engineer at Coco impact urban logistics?

The role of a Founding Machine Learning Engineer at Coco is pivotal in transforming urban logistics. By developing autonomous systems that optimize delivery routes and improve delivery times, you'll directly contribute to enhancing local economies and customer experiences. Your work will play a crucial part in enabling our robots to operate more efficiently, benefiting urban communities.

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What kind of projects will I work on as a Founding ML Engineer at Coco?

As a Founding Machine Learning Engineer at Coco, your projects will include developing cutting-edge machine learning and AI systems for our autonomous delivery robots. This will entail designing data pipelines, enhancing decision-making processes, and simulating various driving scenarios—ensuring that our innovative solutions meet real-world application needs.

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Common Interview Questions for Founding ML Engineer
Can you explain a machine learning project you've worked on relevant to autonomous systems?

In responding to this question, outline a specific project focused on autonomous systems. Describe your role, the algorithms you used, the challenges you overcame, and the impact the project had on the system's performance. Highlight metrics that showcase your project's success, such as accuracy rates.

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What experience do you have with sensor fusion and its importance in autonomous vehicles?

Sensor fusion is crucial for improving the reliability of data from various sensors. Discuss how you've implemented sensor fusion techniques in past projects. Explain how combining data from LiDAR, cameras, and other sensors enhances object detection and overall vehicle perception.

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How do you approach the development of deep learning models?

Discuss your systematic approach to developing deep learning models. Start with data collection and preprocessing, explain your model architecture choices, and talk about the training processes you implement. Emphasize validation techniques you use to ensure the model's robustness against real-world data.

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What programming languages and tools are you proficient in and how have you used them in ML projects?

Mention Python and C++ as your core languages, highlighting any frameworks you utilize like PyTorch for model training. Provide examples of projects where you implemented these tools, emphasizing the specific challenges each tool helped you overcome.

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How do you ensure the safety and reliability of your machine learning models in autonomous systems?

Outline the techniques you use, such as redundancy checks and thorough testing in simulated environments. Discuss the importance of adhering to safety standards and regulations, and describe any experiences you have integrating safety mechanisms into machine learning models.

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Can you discuss a time when you had to debug a complex machine learning model?

Share a specific example where you faced issues with a model. Detail the debugging steps you took, including the tools and methods you used to identify and fix the problems. Highlight how your solutions improved the model’s performance.

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What role does simulation play in developing autonomous robot systems?

Discuss the significance of using simulation for testing various scenarios and conditions that robots may encounter. Emphasize your experience creating simulation environments to validate models before real-world deployment, thus reducing risks and improving safety.

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How do you stay updated on advancements in machine learning and robotics?

Explain your strategies for staying current with industry trends, such as following relevant journals, attending conferences, or participating in online forums. Highlight any specific resources like academic papers or influential thought leaders in machine learning and robotics that you follow.

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How would you handle divergent opinions within a team while working on an ML project?

Emphasize the importance of fostering open communication and collaboration. Share your approach of facilitating discussions to weigh all ideas objectively and ensure the team's consensus while keeping the project goals in focus.

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Why do you want to work at Coco as a Founding ML Engineer?

Discuss your passion for urban logistics and the impact you hope to make in enhancing delivery experiences. Mention how Coco's mission aligns with your values and expertise, and highlight your enthusiasm for contributing to pioneering solutions in the autonomous domain.

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Full-time, on-site
DATE POSTED
December 24, 2024

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