Edge ML Engineer for Farm Robotics & Data Infra

Orchard Robotics; San Francisco (CA); On-site; USD 100,000 - 130,000; Full time

Benefits offered by this job

Generous equity compensation

Comprehensive Health, Vision, and Dental coverage

Dynamic work environment with a close-knit team

Job summary

A technology startup in California is seeking a Machine Learning Engineer to develop robust solutions for ML/CV software relating to farm image data. The role involves building scalable ETL pipelines and collaborating with a dedicated team. An ideal candidate has 2+ years of experience, proficiency in Python, and knowledge of data engineering tools and cloud platforms. This full-time, in-person position offers comprehensive benefits, equity compensation, and a chance to make a significant impact on farming efficiency.

Qualifications

• 2+ years of industry experience building production-grade data pipelines and ML infrastructure.
• Ability to work independently, learn quickly, and adapt in a dynamic environment.
• Familiarity with MLops software and data engineering for consistent model deployment.

Responsibilities

• Build scalable ETL pipelines for processing large image datasets.
• Develop infrastructure for model training, evaluation, and inference.
• Collaborate with agronomists to translate crop biology into ML features.

Skills

Python

ML frameworks (e.g., PyTorch)

Data engineering (e.g., Pandas, SQL)

Cloud platforms (AWS, GCP)

Containerization (Docker, Kubernetes)

Tools

MLFlow

WandB

Job description

A technology startup in California is seeking a Machine Learning Engineer to develop robust solutions for ML/CV software relating to farm image data. The role involves building scalable ETL pipelines and collaborating with a dedicated team. An ideal candidate has 2+ years of experience, proficiency in Python, and knowledge of data engineering tools and cloud platforms. This full-time, in-person position offers comprehensive benefits, equity compensation, and a chance to make a significant impact on farming efficiency.