Aquabyte
Aquabyte4mo ago
USD 130000–170000/yr

Machine Learning Engineer

San Francisco Bay AreaFull-Timemid
Data ScienceMachine Learning EngineerData & AI
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Quick Summary

Overview

Aquabyte is seeking a Machine Learning Engineer to help develop and deploy new algorithms to fish farms across the world.

Technical Tools
Data ScienceMachine Learning EngineerData & AI
Aquabyte is seeking a Machine Learning Engineer to help develop and deploy new algorithms to fish farms across the world. You’ll be responsible for software and machine learning model development of our on-camera and cloud software.
 
Our mission
Aquabyte is on a mission to revolutionize the sustainability and efficiency of aquaculture. It is an audacious, and incredibly rewarding mission. By making fish farming more efficient and viable, we aim to promote healthy (for the fish and environment) production of low carbon protein and mitigate one of the biggest causes of climate change. Aquaculture is the single fastest growing food-production sector in the world, and now is the time to define how technology is used to harvest the sea and preserve it for generations to come.
 
We are a diverse, mission-driven team that is eager to work alongside kindred spirits. If this vision inspires you please get in touch.
 
Our product
We are currently focused on helping salmon farmers better understand their fish population and make environmentally sound decisions. Through custom underwater cameras, computer vision, and machine learning we are able to quantify fish weights, detect the health status, and generate optimal feeding plans in real time. Our product operates at three levels: on-site hardware for image capture, cloud pipelines for data processing, and a user-facing web application. As a result, there are hundreds of moving pieces and no shortage of fascinating challenges across all levels of the stack.
 
Above all, Aquabyte is a customer-driven company. Our product development is dictated by the needs of fish farmers and we prioritize customer delight in everything we do. We are committed to building a global, collaborative team.
 
The role
As a Machine Learning Engineer you will be responsible for developing Machine Learning models and pipelines as well as interacting with databases and data infrastructure. Conducting in-depth data analytics and building statistical data inference models of biological processes. This role is on the AI team where we develop image and video inference pipelines to estimate the weight, health and behavior of individual fish and fish populations. You will work closely alongside engineers with years of industry and academic experience.
  • BS/MS in relevant technical degree
  • 3+ years of experience with data-science
  • Strong coding ability; strong grasp of Python, SQL
  • Strong data analytics & modeling & ML skills
  • Strong data pipeline and data management skills
  • Strong software engineering skills; knowledge of best practices, testing, and deployment
  • Familiarity with; snowflake, dbt, airflow, pandas
  • Experience with Docker and cloud SW development (i.e. AWS)
  • Competitive salary
  • Unlimited vacation policy
  • Flexible working hours
  • Medical, vision, & dental insurance
  • Retirement matching plan
  • Potential travel to Norway
  • Evolve in a fast-paced environment
  • Be able to shape a business in its early days
  • Get ideas, feedback, and suggestions from other best-in-their-field colleagues
  • Mentorship opportunities, we'll be dedicated to investing in you and supporting you as you grow
  • Listing Details

    Posted
    December 5, 2025
    First seen
    March 26, 2026
    Last seen
    April 22, 2026

    Posting Health

    Days active
    27
    Repost count
    0
    Trust Level
    44%
    Scored at
    April 23, 2026

    Signal breakdown

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    Aquabyte

    Aquabyte revolutionizes fish farming with advanced AI-driven camera systems for real-time monitoring of fish health and welfare.

    Employees
    125
    Founded
    2017
    View company profile
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    AquabyteMachine Learning EngineerUSD 130000–170000