Machine Learning Engineer

ABOUT FLOVISION

FloVision is a remote-first startup focused on improving the food supply chain, starting with protein processing. We design computer vision and machine learning-assisted production processes to reduce food waste, improve QA, and enhance staff skills, using proprietary hardware and software to solve customer problems.

FloVision is a U.S.-based Series A startup with a remotely distributed team across the USA, UK and Ireland.
POSITION OVERVIEW

As a Machine Learning Engineer at FloVision, you will design, develop, and optimize computer vision models and deep learning capabilities across our product portfolio. Rather than working on a single product, you’ll contribute to projects throughout the company, collaborating with machine learning, software, hardware, product, and data annotation teams to bring reliable, production-ready solutions to market.

As an early member of our engineering team, you’ll work across the machine learning lifecycle - from data collection, annotation, and validation to experimentation, model development, deployment, and performance monitoring. You’ll help build high-quality datasets, strengthen data integrity, validate model results, and ensure our models deliver meaningful outcomes in real-world production environments. You’ll also have the opportunity to influence our technical direction, product roadmaps, and engineering culture.

We’re looking for an adaptable, self-motivated engineer who can take ownership of new projects, thrive in an evolving startup environment, and contribute meaningfully to our mission of eliminating food waste and reducing global CO₂ emissions by 1%.
LOCATION & TRAVEL

This is a remote position aligned with U.S. Central working hours. Travel is a regular and essential part of the role, accounting for up to 10% of your time, including company team summits. Travel may include:

- Site visits for onboarding or educational purposes

- On-site data collection for model training and validation

- R&D visits to one of our in-person workshops/facilities

- 1-2 in-person team meetups per year

Candidates should be comfortable working in active production environments that may be greasy, loud, cold, and physically demanding. Most travel will be within the United States, although occasional international travel may be required. Some trips may be scheduled with only one or two days’ notice, but we provide advance notice whenever possible. Comp days are provided when weekend travel is required.
KEY RESPONSIBILITIES

- Build and maintain ETL pipelines that prepare structured and unstructured data for machine learning applications

- Clean datasets and perform feature engineering to support model development.

- Annotate and review image data throughout the machine learning workflow (This is a core responsibility of the role, not a secondary task)

- Use Python, SQL, and statistical analysis to explore data and uncover actionable insights

- Train, fine-tune, evaluate, and experiment with deep learning models, primarily for computer vision applications

- Own machine learning outcomes end to end - from data quality and model performance to deployment and measurable product impact

- Collaborate with the annotation team to improve data quality, labeling practices, and machine learning workflows

- Partner with machine learning and software engineering teams to productionize, deploy, and monitor models

- Help make machine learning processes, capabilities, and results accessible to teams across the company

- Make sound technical decisions independently and drive projects forward with a high degree of autonomy

REQUIRED QUALIFICATIONS

- Bachelor’s degree in computer science, engineering, mathematics, or a related field - or equivalent practical experience

- Three or more years of experience across the machine learning or data science lifecycle, with a focus on computer vision

- Experience applying semantic segmentation to a real-world business or production use ca