Applied ML Engineer

About Acast
Since 2014, Acast has been building the world's most valuable podcast marketplace, creating the technology that connects podcast creators, advertisers, and listeners. Its marketplace spans more than 140,000 podcasts, 3,300 advertisers, and one billion quarterly listens. Crucially, those listens are monetized wherever they happen—across any podcast app or listening platform.

About the role
We are looking for a Software Engineer for the Acast Intelligence team, specialising in data engineering within the machine learning space. The ideal candidate would be able to build things like a modern recommendation engine, truly understanding it instead of just piecing it together, probably thanks to a solid background in statistics or related fields. We're after someone who can cut through the hype, focus on real value that LLMs and related tech can bring, and always keep their eyes on the prize: driving growth for our company and our marketplace's users.

Team's scope

The team is focused on recommendation systems and intelligent automation. Our product vision is a set of connected systems that turn deep and broad data into decisions and reduce friction, helping one person achieve as much as five would. We build to enable podcast creators to grow their audience, advertisers to be matched to creators, and internal teams to focus on what matters most instead of getting bogged down in chasing data.
This work has a company-wide impact.

Team composition and tools

The team is small but made up of seasoned engineers. We deploy on AWS, and most of our company's code is in TypeScript, including the infrastructure, but some of this particular team's code is in Python for the reasons you'd expect. We collaborate on our projects and keep the work process light. Our PM knows the space in and out. We've shipped the first version of a recommendation engine, and there's plenty more in the pipeline. There aren't many established best practices or ready answers in this field, so the work is a lot about experimentation and learning.

Experience we're looking for

• Background and interest in some of the following: statistics, machine learning, LLMs, recommendation systems, RAG systems (experience with their evaluation is a plus)
• Proficiency in Python, familiarity with TypeScript (or the other way around)
• Familiarity with vector databases
• A habit of staying up to date in a seriously evolving field
• Experience with or interest in learning AWS
• Experience building software that's actually delightful for the users
• A pragmatic mindset for making sensible trade-offs
• Interest in podcasts is really optional, but if you have it, this job will be so much more fun

Logistics

We are remote-first but prefer to have teams in similar timezones; for this team, this means an overlap of at least 4 hours with CET (UTC+1). 

• For this role we're hiring within Sweden or UK, and therefore applicants will need to have the right to work in one of these locations.

Culture 

Acast is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment regardless of race, gender, sexual orientation, religion, ethnicity, national origin or any of the other wonderful characteristics that make us different.

Culture is our number one priority as a business. We believe people come first, and we work every day to enable autonomy, continuous improvement and bring out the best in people. We're global and have remote teams, so it's even more important that we strive for an open, inclusive and caring environment where everyone feels visible and welcome. 

We consider ourselves a modern organization driven by strong values to create the best, most fulfilling and nurturing culture.

We very much look forward to finding the next great person to join our cause