Machine Learning Engineer
Build scalable ETL pipelines and ML infrastructure for processing massive farm image datasets from tractor-mounted cameras. Develop edge-deployed computer vision models for yield estimation, disease detection, and crop analysis using PyTorch and cloud tools, with 2+ years experience.
About the job
Responsibilities
- Build and maintain scalable ETL pipelines for processing large, diverse image datasets collected from tractor-mounted camera systems in farms.
- Develop and deploy infrastructure for model training, evaluation, and inference, both in the cloud and on edge devices.
- Design and implement intelligent active sampling infrastructure to optimize data collection and improve model performance.
- Stay up-to-date with current literature in computer vision models and architectures, and apply relevant advancements to our systems.
- Collaborate with a multidisciplinary team to integrate ML solutions into production robotics systems.
- Work closely with agronomists and farmers to understand crop biology and translate domain knowledge into actionable ML features.
- Be a generalist, supporting different parts of our software stack as needed.
Requirements
- 2+ years of real-world, industry experience building production-grade data pipelines and ML infrastructure.
- Proficiency in Python and experience with ML frameworks (e.g., PyTorch).
- Strong experience with data engineering tools (e.g., Pandas, SQL, MLFlow, WandB).
- Familiarity with cloud platforms (AWS, GCP) and containerization (Docker, Kubernetes).
- Experience working with massive amounts of real-world training data.
- Familiarity with MLOps software and data engineering to ensure consistent deployment of ML models.
- Ability to work independently, learn quickly, and operate in a dynamic environment.
- Enthusiasm for taking on multiple roles and responsibilities as our company grows.
Nice-to-Haves
- Experience deploying & optimizing ML models to run fast on embedded compute like NVIDIA Jetson.
- Experience prototyping, evaluating, or deploying new ML/CV models on the edge.
Compensation & Benefits
- Full-time, in-person role at our San Francisco or Seattle office.
- Generous equity compensation.
- Comprehensive Health, Vision, and Dental coverage (100% premium covered).
Skills
PyTorch, pandas, SQL, MLflow, Wandb, AWS, GCP, Docker, Kubernetes, MLOps, Nvidia Jetson
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