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TerraClear

Machine Learning Engineer

Reposted 4 Days Ago
Remote
Hiring Remotely in USA
150K-220K Annually
Mid level
Remote
Hiring Remotely in USA
150K-220K Annually
Mid level
The Machine Learning Engineer will design and deploy computer vision models, build training pipelines, and enhance ML infrastructure to improve agricultural field operations.
The summary above was generated by AI

TerraClear applies artificial intelligence, robotics, and world-class mechanical design to solve some of the most data deficient and labor intensive jobs on the farm. These technologies are rapidly transforming agricultural intelligence, allowing farmers to make faster and more informed decisions that translate into highly precise actions and more productive farms. Our first application solved one of the most disliked tasks on the farm: clearing rocks. The annual emergence of news rocks impacts nearly half of farms in North America, slowing farming, damaging equipment, and causing downtime during seeding and harvesting. Solving this problem frees farmers to focus on higher-value tasks and brings their operations into a new era of farming.

Leveraging our commercial success in rocks, we are now expanding our core technologies to new farm applications including the precise management of weeds, pests, disease and overall plant health. 

Our team is tight-knit and believes in the power of teamwork. We value learning directly from the farmers we serve, getting our hands dirty, and tackling tough challenges together. You will thrive at TerraClear with a positive attitude, a collaborative mindset, a healthy dose of grit and a passion for solving real-world problems.

As a Machine Learning Engineer, you will design, train, evaluate, and deploy deep learning models for real-world computer vision applications across mapping intelligence and robotics systems.

This is a hands-on engineering role. You will write production code, build scalable training pipelines, and improve ML infrastructure. You’ll collaborate closely with other ML engineers, software engineers, and product stakeholders to continuously improve model performance in real-world environments.

Our systems operate in challenging environments where robustness, generalization, and performance matters. The models you build will directly impact field operations and autonomous decision-making.

In this role you will:

  • Design and train modern computer vision models (CNNs, Vision Transformers, foundation models) to solve novel perception tasks
  • Build and maintain scalable training pipelines using PyTorch and HPC infrastructure (e.g., Slurm, distributed training)
  • Develop data curation and active learning workflows
  • Optimize models for deployment (ONNX, TensorRT, containerization)
  • Test and validate models in both cloud and edge environments
  • Build reproducible experimentation workflows (version control, experiment tracking, configuration management)
  • Drive experimental cycles: define hypotheses, implement techniques from literature, evaluate results, and present recommendations
  • Translate research ideas into production-ready implementations
  • Design, implement, and test ML-related components and supporting software
  • Perform statistical analysis and fine-tune model performance based on production and field feedback

What we’re looking for:

Required 

  • 3+ years of full-time professional experience in computer vision-focused machine learning (not student internship)
  • Strong PyTorch experience, including custom layers, loss functions, datasets, dataloaders, and training loops
  • Experience with modern vision architectures (CNNs, ViTs, DETR-style models, foundation models)
  • Experience building or contributing to production ML systems
  • Solid software engineering fundamentals (testing, version control, clean code principles)
  • Strong communication skills and ability to explain complex technical topics clearly
  • Engineering degree or equivalent practical experience

Preferred

  • Experience deploying models to edge devices (Jetson, embedded GPUs, mobile platforms)
  • Experience with AWS or similar cloud infrastructure
  • Experience with Docker and containerized ML workflows
  • Familiarity with robotics or perception systems
  • Experience owning or contributing to a production model that delivered business value

Compensation Range = $150-220K, commensurate with experience. No H1-B sponsorship available.

We offer competitive compensation and benefits to our full-time regular employees, including:

  • Pre-IPO stock options (tax-advantaged ISOs)
  • Competitive base salary
  • Medical, dental, and vision insurance - 100% of premiums paid for employees and 85% of premiums paid for dependents
  • Generous paid time off and holidays 
  • 401(k) Plan
  • An inclusive and tight company culture that is mission driven

If you’re excited about TerraClear, fit the above qualifications and are passionate about solving hard problems, please apply now!

TerraClear is an Equal Opportunity Employer committed to fostering an inclusive culture with extraordinary employees. We provide employment opportunities without regard to any legally protected status. If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.

Top Skills

AWS
Docker
Onnx
PyTorch
Slurm
Tensorrt

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