Senior ML Engineer

As a Senior ML Engineer at Equiforte, you will develop, train, and deploy the machine learning models that power automated financial reporting, data extraction, and analytics for private capital firms. This is not a generic ML role — you will work on domain‑specific models where precision matters above all else: extracting financial figures from unstructured documents, normalizing heterogeneous portfolio data, generating narrative performance commentary, and detecting anomalies in fund‑level financials.

What you'll do

• Design and train ML and LLM‑based models for financial document extraction — capital call notices, fund administrator reports, portfolio company financials, and limited partnership agreements
• Build and maintain the ML infrastructure that serves models in production with low latency and high reliability
• Own the evaluation frameworks that measure model accuracy on financial extraction tasks, where correctness requirements far exceed general‑purpose benchmarks
• Collaborate with Platform Engineers to integrate ML outputs into the core reporting pipeline
• Research and adapt state‑of‑the‑art techniques in document understanding, information extraction, and generative AI to the private capital domain
• Build the internal tooling that allows the team to iterate quickly on training data, evaluation, and model versions

This role reports to the VP of Engineering and works closely with the Platform Engineering and Product teams.

What We're Looking For

Requirements

• 5+ years of professional ML engineering experience, including production model deployment
• Strong proficiency in Python and modern ML frameworks (PyTorch or JAX preferred)
• Experience fine‑tuning and deploying large language models or document understanding models
• Hands‑on experience building evaluation pipelines and managing training data quality
• Familiarity with information extraction, named entity recognition, or structured prediction from unstructured text
• Experience operating ML systems in production — monitoring, retraining, and versioning
• Strong written communication skills for design documents and async technical discussion

Nice to Have

• Experience in financial services, fintech, or fund administration
• Familiarity with private capital concepts (NAV, waterfalls, capital calls, LP reporting)
• Experience with RAG architectures and vector retrieval systems
• Background in document AI, OCR pipelines, or PDF extraction
• Experience at a high‑growth startup building ML systems from early stage
• Contributions to open‑source ML projects or published research