ML/AI and Data Engineer
About Blueberries.
Blueberries. is building the next generation of AI-driven FP&A automation, enabling real-time financial visibility, automated data collection, and intelligent cost allocation using modern AI and data processing technologies. With strong early traction, including design partners, LOIs, and growing industry demand, we’re scaling our engineering team as we build our MVP.
About the Role
We are looking for an ML/AI & Data Engineer to model clients’ financial structures, costs, and incomes from their emails, internal documents, and heterogeneous text and tabular data, and to map these costs and incomes onto the financial structure. You will work mostly from scratch and deploy on AWS. We operate with an MVP mindset: simple, functional, fast-to-market solutions built by a small, high-performing engineering team. We expect strong practices in versioning, testing, automation, and communicating clearly while working in small, testable increments. You will work closely with our SaaS product team to display your extracted insights in a client-facing dashboard.
Responsibilities
- Build and maintain ETL pipelines to collect, clean, and structure client data
- Implement document vectorization workflows
- Apply NLP and LLM models on documents to extract structured, actionable insights
- Develop unsupervised models to infer a company’s financial structure
- Design custom algorithms to align extracted data with a company’s hierarchy and financial model
- Optionally handle AWS deployments, infrastructure orchestration, and service connectivity (if no cloud engineer is present)
- Collaborate with the product/dashboard team to surface insights in a usable, intuitive way
- Maintain strong engineering standards in testing, versioning, automation, and documentation
Required Skills & Experience
- Experience with embeddings and vector databases
- Strong background working with NLP models and LLMs (local inference and/or API-driven)
- Proven experience building data pipelines and processing workflows
- Strong R&D mindset; ability to create custom solutions beyond off-the-shelf tools
- Experience with AWS cloud services, setup, orchestration, and deployments
- Experience with automation or data acquisition tools (n8n, Zapier, browser-based scraping)
- Strong communication and organizational skills
- Ability to work flexible hours when needed
- Autonomous, pro-active, and execution-driven
Bonuses
- Experience with AI applied to finance, FP&A, or enterprise data
- Experience with event-driven architectures or microservices
- Background in unsupervised learning on enterprise datasets