This role is based out of our Amsterdam office or London office
We are an office-first company & believe great products are made when we are together.
About Stacks
At Stacks were transforming the way finance teams approach one of their most critical processes: the monthly close. For mid to large enterprises the close is a painstaking manual effort that pulls finance teams away from strategic initiatives to focus on repetitive tedious tasks. We believe this needs to change.
Our vision is bold. With the power of AI were reimagining the monthly close to be as simple as a single clickproviding the most accurate detailed financial insights on day one of each month. By giving finance teams their time back we enable them to focus on high-impact strategic work that drives their companies forward.
Our team is a blend of finance product and technical experts from top-tier companies like Uber Plaid Miro Mollie and Bunq united by the drive to create a game-changing solution. Based in the heart of Amsterdam our office offers inspiring views over the iconic canals. Backed by leading VCs and executives from Stripe Plaid and OpenAI were ready to reshape the future of finance.
About the Role
Were looking for a Staff AI Engineer to spearhead our AI and ML efforts. This is far from a typical engineering role - its an opportunity to build our machine learning and data function from the ground up. Financial data can be a goldmine thats often buried and untapped and we need someone with the expertise and tenacity to unlock its full value.
You will be at the forefront developing cutting-edge solutions to automate financial close workflows and surface key strategic insights. Beyond tackling fascinating machine learning challenges youll also handle the foundational work - designing robust data pipelines and transforming messy unstructured data into clean valuable assets. If youre passionate about diving deep into data revel in both the glamorous and gritty aspects of ML and want to make a significant impact on our product and company trajectory this role is for you.
What Youll Do
Build and Optimize AI Agents
Develop and refine autonomous agents leveraging generative AI to automate financial workflows - from data ingestion to decision support.
Design and Fine-Tune ML Models
Train evaluate and deploy models for forecasting predictive analysis and transaction categorization ensuring robust and reliable results.
Engineer Data Pipelines
Construct and optimize data pipelines for raw structured and unstructured data ensuring high-quality inputs power our models and AI agents.
Leverage Generative AI
Incorporate advanced transformer-based architectures and embedding techniques to drive automation enhance insights and deliver impactful outcomes.
Performance Testing & Benchmarking
Rigorously validate model performance run data validation and diagnostics and ensure flawless operations in production environments.
About You
5 Years of Experience
Background as a Data Scientist Data Engineer or ML Engineer with a history of delivering high-impact machine learning solutions.
Financial Domain Expertise
Familiar with forecasting predictive modeling and transaction-oriented analytics - ideally within the finance sector.
Technical Fluency
Proficient in Python and experienced in deploying ML models to production. Hands-on with modern ML frameworks and data engineering tools.
Entrepreneurial Mindset
Comfortable tackling complex unstructured problems and thriving in a fast-paced high-growth environment.
Vision and Drive
You set ambitious goals pursue innovative solutions and arent afraid to challenge the status quo.
User-Centric
You prioritize customer needs and have a strong product intuition ensuring AI solutions translate to real business value.
Adaptable
You excel in rapidly changing settings and love learning new skills and technologies.
Continuous Learner
You stay updated on cutting-edge methodologies best practices and industry trends to refine your craft.
Bonus: Experience working on automation business intelligence or process optimization within a finance team.
Whats in It for You
Cutting-Edge Technology: Work at the forefront of the Gen AI revolution.
Top-Tier Team: Collaborate with talented colleagues from companies like Uber Plaid Miro and Mollie.
Foundational Role: Become one of the founding pillars of an exciting company backed by Tier 1 VCs and executives from OpenAI Stripe and DeepMind.
Inspiring Workspace: Enjoy the view of the Amsterdam canals in our stunning office.
The Process
Step 1: 30-minute screening call with our talent partner (Peter) to discuss your background motivation experience and practical details.
Step 2: 30-minute call with our founder (Albert) to learn more about you and share more about our product.
Step 3: 45-minute call with a team member (Ivan) to dive deeper into your experience;
Step 4: Take-home and 1-hour on-site panel interview with our team at Stacks.
Step 5: 3 x team members to get to know each other better.
Step 6: Offer!
Required Experience:
Staff IC
This role is based out of our Amsterdam office or London office We are an office-first company & believe great products are made when we are together.About StacksAt Stacks were transforming the way finance teams approach one of their most critical processes: the monthly close. For mid to large ente...
This role is based out of our Amsterdam office or London office
We are an office-first company & believe great products are made when we are together.
About Stacks
At Stacks were transforming the way finance teams approach one of their most critical processes: the monthly close. For mid to large enterprises the close is a painstaking manual effort that pulls finance teams away from strategic initiatives to focus on repetitive tedious tasks. We believe this needs to change.
Our vision is bold. With the power of AI were reimagining the monthly close to be as simple as a single clickproviding the most accurate detailed financial insights on day one of each month. By giving finance teams their time back we enable them to focus on high-impact strategic work that drives their companies forward.
Our team is a blend of finance product and technical experts from top-tier companies like Uber Plaid Miro Mollie and Bunq united by the drive to create a game-changing solution. Based in the heart of Amsterdam our office offers inspiring views over the iconic canals. Backed by leading VCs and executives from Stripe Plaid and OpenAI were ready to reshape the future of finance.
About the Role
Were looking for a Staff AI Engineer to spearhead our AI and ML efforts. This is far from a typical engineering role - its an opportunity to build our machine learning and data function from the ground up. Financial data can be a goldmine thats often buried and untapped and we need someone with the expertise and tenacity to unlock its full value.
You will be at the forefront developing cutting-edge solutions to automate financial close workflows and surface key strategic insights. Beyond tackling fascinating machine learning challenges youll also handle the foundational work - designing robust data pipelines and transforming messy unstructured data into clean valuable assets. If youre passionate about diving deep into data revel in both the glamorous and gritty aspects of ML and want to make a significant impact on our product and company trajectory this role is for you.
What Youll Do
Build and Optimize AI Agents
Develop and refine autonomous agents leveraging generative AI to automate financial workflows - from data ingestion to decision support.
Design and Fine-Tune ML Models
Train evaluate and deploy models for forecasting predictive analysis and transaction categorization ensuring robust and reliable results.
Engineer Data Pipelines
Construct and optimize data pipelines for raw structured and unstructured data ensuring high-quality inputs power our models and AI agents.
Leverage Generative AI
Incorporate advanced transformer-based architectures and embedding techniques to drive automation enhance insights and deliver impactful outcomes.
Performance Testing & Benchmarking
Rigorously validate model performance run data validation and diagnostics and ensure flawless operations in production environments.
About You
5 Years of Experience
Background as a Data Scientist Data Engineer or ML Engineer with a history of delivering high-impact machine learning solutions.
Financial Domain Expertise
Familiar with forecasting predictive modeling and transaction-oriented analytics - ideally within the finance sector.
Technical Fluency
Proficient in Python and experienced in deploying ML models to production. Hands-on with modern ML frameworks and data engineering tools.
Entrepreneurial Mindset
Comfortable tackling complex unstructured problems and thriving in a fast-paced high-growth environment.
Vision and Drive
You set ambitious goals pursue innovative solutions and arent afraid to challenge the status quo.
User-Centric
You prioritize customer needs and have a strong product intuition ensuring AI solutions translate to real business value.
Adaptable
You excel in rapidly changing settings and love learning new skills and technologies.
Continuous Learner
You stay updated on cutting-edge methodologies best practices and industry trends to refine your craft.
Bonus: Experience working on automation business intelligence or process optimization within a finance team.
Whats in It for You
Cutting-Edge Technology: Work at the forefront of the Gen AI revolution.
Top-Tier Team: Collaborate with talented colleagues from companies like Uber Plaid Miro and Mollie.
Foundational Role: Become one of the founding pillars of an exciting company backed by Tier 1 VCs and executives from OpenAI Stripe and DeepMind.
Inspiring Workspace: Enjoy the view of the Amsterdam canals in our stunning office.
The Process
Step 1: 30-minute screening call with our talent partner (Peter) to discuss your background motivation experience and practical details.
Step 2: 30-minute call with our founder (Albert) to learn more about you and share more about our product.
Step 3: 45-minute call with a team member (Ivan) to dive deeper into your experience;
Step 4: Take-home and 1-hour on-site panel interview with our team at Stacks.
Step 5: 3 x team members to get to know each other better.
Step 6: Offer!
Required Experience:
Staff IC
View more
View less