ML Software Engineer III Barn Owl Precision Agriculture

Fremont Economic Development Corporation; Florence (CO); On-site; USD 145,000 - 175,000; Full time

Benefits offered by this job

Equity participation

Hands-on innovation

Mission-driven work

Job summary

Fremont Economic Development Corporation is seeking a Software Engineer III (Machine Learning) to lead the development of perception and ML systems for autonomous robots. This position demands 8+ years in software engineering and proficiency in Python, with a strong background in machine learning and computer vision. You will design and optimize ML models while ensuring reliable performance across farming environments. The role offers remote work for exceptional candidates and competitive compensation of $145k-175k plus equity participation.

Qualifications

• 8+ years of professional software engineering experience with hands-on ML systems.
• Strong proficiency in Python and deep experience with modern ML frameworks.
• Proven track record of deploying ML models into reliable, production-grade systems.

Responsibilities

• Own the design and optimization of computer vision models for real-time performance.
• Lead model optimization for latency, memory, and hardware acceleration.
• Debug and resolve production ML issues in-field, driving rapid iteration.

Skills

Python

Machine Learning frameworks

Computer Vision fundamentals

Model evaluation

Tools

ROS2

Jetson/AGX

Job description

Location: Florence, CO or Denver/Boulder. Remote considered for exceptional candidates. Job Type: Full-Time Compensation: $145k-175k + meaningful equity participation

About Barn Owl Precision Ag (BOPA)

At BOPA, we’re building the future of autonomy for small and mid-sized farms. Our compact, intelligent robots (ANTs) perform precision agricultural tasks like weeding, planting, and nutrient management - helping farmers cut labor costs, reduce chemical use, and increase sustainability.

We are a Seed-stage startup with a nimble, farmer-focused team. Our goal is to design robust, scalable robotics systems that can be deployed across the globe.

Role Overview

We’re looking for a Software Engineer III (Machine Learning) to take a leading role in building and scaling the perception and ML systems behind our ANT platform.

This is a senior applied ML engineering role focused on production impact. You’ll own major parts of the ML lifecycle end-to-end - from dataset and model iteration to edge deployment, in-field validation, and long-term system reliability. You’ll work closely with robotics, autonomy, and field teams to ensure our ML systems perform under the messy, variable conditions of real farms, not just in controlled environments.

Beyond strong individual contribution, this role requires technical leadership: raising the quality bar for ML engineering, driving sound design decisions, and helping evolve the tooling, architecture, and practices needed to scale ML across our platform. Your work will directly shape how ANTs perceive the world and act on it safely, accurately, and consistently in production.

Key Responsibilities

ML Development & Deployment

Own the design and optimization of computer vision models for real-time performance on edge devices

Lead model optimization for latency, memory, and hardware acceleration

Define evaluation frameworks and ensure performance translates to real-world field conditions

Debug and resolve production ML issues in-field, driving rapid iteration

Shape ML system architecture, experimentation, and reproducibility

Data & Model Lifecycle

Own the end-to-end data lifecycle - collection, labeling, curation, and versioning

Define data strategies to improve model performance, including edge case discovery and feedback from field data

Ensure high-quality datasets with strong coverage across real-world conditions

Software Engineering

Write and maintain production-quality software with appropriate testing, logging, and observability to support reliable ML-driven systems

Improve system performance, scalability, and reliability across the ML stack

Lead debugging and root cause analysis across ML, data, and system-level issues

Set and uphold engineering best practices, including testing, code quality, and documentation

System Integration & Robotics

Integrate ML models into the robotics stack (ROS2), ensuring reliable real-time performance on edge hardware (Jetson/AGX)

Work closely with the hardware team to ensure seamless interaction between perception and actuation

Optimize end-to-end system performance across sensing, inference, and decision-making loops

Debug and resolve system-level issues across ML, sensors, and robotics pipelines in both lab and field environments

Success Metrics (First 12-18 Months)

Successfully deploy and iterate on ML models used in production ANT field operations

Improve perception accuracy and robustness across multiple crops and environments

Maintain a reliable ML pipeline that evolves in line with production data

Reduce field issues caused by ML failures through better testing and iteration

Improve end-to-end autonomy performance by delivering dependable ML components

Required Qualifications

8+ years of professional software engineering experience with hands‑on ML systems

Strong proficiency in Python and deep experience with modern ML frameworks

Proven track record of deploying ML models into reliable, production‑grade systems

Deep understanding of CV fundamentals, model evaluation, and real‑world performance tradeoffs

Ability to design and own software components that support ML‑driven systems at scale

Comfortable operating in ambiguity, working with real‑world data, and driving iterative, field‑driven development

Bonus Points

Experience with object detection or segmentation models (e.g. YOLO or similar)

Familiarity with edge deployment and model optimization for constrained hardware

Exposure to robotics, autonomy, or real‑time systems

Experience working with ROS2 or integrating ML into larger distributed systems

Background in outdoor, agricultural, or other field‑deployed ML systems

Our Culture

At BOPA, we value practical impact, humility, and speed of iteration. We test everything in the field, learn fast, and build with farmers. We believe diverse perspectives lead to better designs, and we’re committed to fostering inclusion and collaboration.

Why Join Us

Mission-Driven Work: Build robots that transform farming and rural economies

Real-World Impact: See your engineering work deployed in active farm operations

Hands-On Innovation: Work directly on full‑stack robotics systems

Fast Learning Curve: Collaborate across hardware, software, and autonomy to expand your technical range, skills and experience

Equity & Growth: Share in the company’s success at scale

**Disclaimer: The duties and responsibilities described above are not a comprehensive list and additional tasks may be assigned to the employee, time to time; the scope of the job may change as necessitated by business demands.