Why This Job is Featured on The SaaS Jobs
Machine Learning engineering roles in SaaS become particularly meaningful when the product depends on real-world signals and must translate them into reliable, customer-facing outcomes. This position sits at the intersection of on-device capture, cloud processing, and a web application, a pattern increasingly common in modern SaaS that blends software delivery with operational data. The emphasis on image and video inference pipelines also reflects how applied AI is being productised beyond pure analytics into ongoing, production-grade services.
For a SaaS career, the work builds durable skills around taking models from experimentation to deployment, then maintaining performance as data shifts over time. Experience spanning Python and SQL, data infrastructure, and software engineering practices maps well to AI-enabled SaaS teams where ML systems are treated as long-lived products. Exposure to pipeline orchestration, data management, and cloud development is also transferable across companies that run multi-tenant platforms and need repeatable, observable ML operations.
This role suits professionals who prefer end-to-end ownership, from data analysis through to production integration, and who enjoy collaborating closely with adjacent engineering disciplines. It will likely appeal to engineers who want their ML work measured by operational impact and system reliability, not only offline metrics.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
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.
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Required Qualifications
- 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
Bonus Qualifications
- Familiarity with; snowflake, dbt, airflow, pandas
- Experience with Docker and cloud SW development (i.e. AWS)
Benefits
- Competitive salary and equity
- 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
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$110,000 - $165,000 a year
Aquabyte takes a market-based approach to compensation. The pay varies on a variety of factors including: job-related qualification, years of experience and competence level, interview performance, and work location.
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At Aquabyte, we admire interesting people with a unique background. We strongly encourage you to apply even if you don’t satisfy all the requirements, and we will get back to you as soon as possible!
