Machine Learning Engineer
6 days ago
Agtonomy is a pioneer in advanced automation and AI solutions for agriculture and beyond. Our innovative TeleFarmer platform addresses labor-intensive needs with automation, transforming conventional equipment into autonomous machines. By partnering with leading manufacturers like Doosan Bobcat, we integrate smart technology into tractors and other machinery, enhancing safety and efficiency. As we expand into ground maintenance and other industrial applications, our expert team continues to address key challenges with labor shortages, sustainability, and profitability across various industries.
The RoleWe are seeking a skilled Machine Learning Engineer to join our Autonomy Team. As a key member of this team, you will play a crucial role in solving challenging perception problems in outdoor vehicle automation. Leveraging your experience, you will implement state-of-the-art ML perception techniques to improve how Agtonomy's tractors perceive and understand the environments where they operate. You will work closely with embedded, localization, and planning engineers on the team to design and evolve the upstream and downstream interfaces of the perception system.
Key Responsibilities:- Apply machine learning to solve challenging perception problems for autonomous systems (e.g., object detection, semantic segmentation, instance segmentation, dense depth, optical flow, tracking, etc.).
- Drive the architecture, deployment, and performance characterization of our deep learning models.
- Refine and optimize models for low-latency inference on embedded hardware.
- Design and build cloud-based training and labeling pipelines.
- Collaborate with the hardware and embedded teams on sensor selection and vehicle packaging given safety requirements.
- Write performant, well-tested software, and improve code quality of the entire Autonomy team through code and design reviews.
- 5+ years of experience in software development for problems involving computer vision, machine learning, and robotic perception techniques.
- Foundational understanding of deep learning: model layer design, loss function intuition, training best practices.
- Experience handling large datasets efficiently and organizing them for training and evaluation.
- Experience curating synthetic and real-world image datasets for training.
- Strong proficiency in modern C++ and Python and experience writing efficient algorithms for resource-constrained embedded systems.
- Ability to thrive in a fast-moving, collaborative, small team environment with lots of ownership.
- Excellent analytical, communication, and documentation skills with demonstrated ability to collaborate with interdisciplinary stakeholders outside of Autonomy.
- An eagerness to get your hands dirty by testing your code on real robots at real customer farms.
- $160,000 - $240,000 per year
- 100% covered medical, dental, and vision for the employee and their dependents
- Commuter Benefits
- Flexible Spending Account (FSA)
- Life Insurance
- Short- and Long-Term Disability
- 401k Plan
- Stock Options
- A collaborative work environment working alongside passionate mission-driven folks
We use a structured interview process to ensure fairness and consistency. The process typically consists of five phases:
- Phone Screen with People Operations (30 minutes)
- Video Interview with the Hiring Manager (45 minutes)
- Coding Challenge and Technical Challenge (1 hour with an Autonomy Engineer)
- Panel Interview (Video interviews scheduled with key stakeholders, each interview will be 30 to 45 minutes)
- Final Interviews (CEO, CFO, VP of Engineering, 30 minutes each)
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