# Senior Machine Learning Engineer

**Company:** [Orchard](https://hotfix.jobs/companies/orchard)
**Location:** San Francisco, CA
**Role:** ML Engineering
**Salary:** $150k – $265k/yr
**Experience:** 5+ years
**Skills:** Python, PyTorch, TensorFlow, pandas, SQL, Apache Airflow, Spark, AWS, GCP, Azure, Docker, Kubernetes, MLOps, Nvidia Jetson, Computer Vision
**Posted:** 2026-03-14

> Senior ML Engineer builds scalable ETL pipelines, develops ML infrastructure for training/evaluation/inference on cloud/edge, and integrates CV models for analyzing farm images from tractor cameras. Requires 5+ years experience with Python, PyTorch/TensorFlow, data engineering tools, and cloud platforms.

## Job Description

## Responsibilities
- Build and maintain scalable ETL pipelines for processing large, diverse image datasets collected from tractor-mounted camera systems in farms.
- Stay up-to-date with current literature in computer vision models and architectures, and apply relevant advancements to systems.
- Develop, deploy, and monitor 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.
- 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 the software stack as needed.

## Requirements
- 5+ years of experience building production-grade data pipelines and ML infrastructure.
- Proficiency in **Python** and experience with ML frameworks (e.g., **TensorFlow**, **PyTorch**).
- Strong experience with data engineering tools (e.g., **Pandas**, **SQL**, **Apache Airflow**, **Spark**).
- Familiarity with cloud platforms (**AWS**, **GCP**, or **Azure**) 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 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
- Generous equity compensation.
- Full-time role at San Francisco, CA office.
- Flexible working hours.
- Comprehensive Health, Vision, and Dental coverage (100% premium covered).

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