Description

Join us at Palm, a well-funded, early-stage fintech startup, on a mission to guide the world’s money flows. As part of our founding team of treasurers, finance specialists, and engineers, you'll help build a world-class treasury management system for enterprises.

Are you ready to build and own the machine learning/data science function from the ground up? Based in Amsterdam or Stockholm and open to mostly remote work? We want to hear from you!

About Palm engineering

Engineering at Palm today consists of a team of five engineers with diverse engineering and cultural backgrounds. We are located in Amsterdam and Stockholm, mostly working remotely with frequent gatherings in one of our locations or at off-sites where it is warmer and sunnier 🏖️

The engineering team has been working together since November 2023 so there is still a lot of opportunities for high impact work as well as playing an important role in further shaping the engineering organisation and culture.

Palm Engineering is defined by our principles:

1. Bias to Action: In the face of uncertainty, we prototype fast and often.
2. Open Communication: We courageously voice concerns to realign our direction as needed.
3. Passion for Challenges: We love the problem and embrace challenges.

In order to achieve this we lean on a culture of collaboration and knowledge sharing, where curiosity, respect and openness are some of our guiding principles. We truly value diversity and are happy to have our perspectives challenged. And of course, let’s have fun together!

Our tech stack

• Data Pipelines: Python, BigQuery
• Database: PostgreSQL
• Cloud: GCP
• Version Control: Git
• We are continuously iterating and exploring technologies as we go - so there’s more to come!

How will you make an impact?

• Our customers need to understand what happened across their bank accounts in the past as well as how balances evolve in the future. We have our first categorization & forecasting models for this. You’ll join as the first Data hire with a broad mandate:
  • Define success metrics for our models
  • Create & evaluate forecasting & LLM models to drive those metrics
  • Build internal tooling to customise models to new enterprise customers
  • Build infrastructure to monitor performance and act on it
  • Build the underlying data infrastructure together with our engineering team (you’ll meet them during the interviews!)
  • Explore new technologies that improve all of the above.
• Collaborate with engineers, designers and founders (they come from Fintech & Treasury!) to understand better what needs to be built and speak up when we are focusing on the wrong things

Our wish list

• There are a lot of different paths into Data. We think you might have:
  • 5+ years of experience in software engineering with 2+ years experience in ML/DS
  • OR 5+ years in business-facing ML/DS with a keen interest in the underlying data infrastructure
• Experience with maintaining production-level ML solutions, with solid software engineering and ML principles
• Strong Python and SQL skills
• Experience with ML frameworks e.g. Tensorflow or PyTorch
• Experience with data analysis libraries e.g. numpy, pandas or jax
• Being proactive and love picking up new things
• Able to collaborate and clearly communicate your ideas
• High sense of ownership
• Nice to Have:
  • Experience with LLM-based features
  • Experience in product improvement and data visualisation.
  • Experience with MLOps

Benefits of working at Palm

• Travel: Meet all your new colleagues at quarterly offsites - the last 3 were in Lisbon, Stockholm & Amsterdam.
• WeWork Membership: Work from home is our go-to - we love spending time with friends and family instead of commuting. We have WeWork memberships for when you want to escape into the city.
• Stock Options: Own a large chunk of Palm and reap the rewards as you help us grow the company to a global player.
  
• Pension & Health Insurance: Best-in-class local insurances and pension schemes so you don't have to worry.
• Wellness Stipend: 500 EUR in annual wellness benefits - gyms, massages, you name it.