Role Overview
We are seeking a visionaryMachine Learning Engineerto design and implement next-generation AI systems that will redefine valuation methodologies in finance. You will work on automating financial data extraction, enhancing qualitative document understanding, and delivering intelligent insights from diverse sources such as financial documents, web data, and third-party platforms.
As a key member of our engineering team, you will collaborate with domain experts in finance and AI to build scalable solutions that address complex challenges in the alternative asset management space.
Impact You'll Make
- Accelerate financial valuation processes by automating complex data extraction and preparation tasks
- Enhance accuracy of investment decisions by ensuring financial data is correctly extracted and processed
- Enable analysts to focus on high-value analysis rather than manual data gathering and formatting
- Create AI-powered tools that surface critical insights from both structured and unstructured financial data
Your Expertise
Programming & Development
Python Mastery : Craft elegant, production-ready code that automates financial data processingML Framework Proficiency : Leverage PyTorch and TensorFlow to build sophisticated data extraction modelsAPI Development : Design and implement robust APIs that integrate with financial platforms and data sourcesFamiliarity with Unix / TerminalFamiliarity with Docker and ContainersEngineering Excellence : Apply Git version control and CI / CD practices to ensure code qualityComputer Vision
Extract financial data from diverse document formats (PDF, Excel, PowerPoint) regardless of layoutWork with OCR systems that accurately capture financial figures and textDevelop models that can extract tabular data from charts (bar, pie, etc.) in financial presentationsCreate table structure recognition systems that understand complex financial statement layoutsDesign document classification systems for organizing diverse financial document typesNatural Language Processing
Build generative AI systems for qualitative understanding of financial documentsImplement text classification and named entity recognition for financial metrics identificationCreate systems that automatically detect dates, periods, currencies, and units in extracted dataDevelop question-answering capabilities that enable chat interfaces with structured financial dataBuild semantic search functionality for financial research and competitive intelligenceData Engineering & MLOps
Design database schemas that efficiently store structured financial dataArchitect pipelines that integrate data from diverse sources (documents, web scraping, third-party APIs)Deploy and monitor models in production environments for critical applicationsLeverage cloud platforms (AWS / Azure / GCP) for scalable data processingYour Responsibilities
Architect and implement machine learning models to automate structured and unstructured data extraction from financial documents (e.g., contracts, balance sheets).Develop natural language processing (NLP) solutions to enhance qualitative document understanding and improve decision-making.Optimize algorithms for scalability and real-time performance across cloud-based platforms.Collaborate with cross-functional teams (finance experts, product managers) to align technical solutions with business objectives.Monitor deployed models to ensure accuracy, efficiency, and adaptability to changing market dynamics.Conduct experiments with state-of-the-art AI techniques to refine model performance and explore innovative applications.Skills
Master's degree in computer science, Data Science, or related field (or equivalent practical experience)Deep software engineering expertise including design patterns, code optimization, and testing best practicesPython programming excellence with a focus on production-quality codeExperience with Git-based workflows and collaborative developmentMLOps capabilities including CI / CD for ML models, workflow automation, and production monitoringCloud platform experience (Azure, AWS, Google Cloud) and containerization expertise (Docker, Kubernetes)Data engineering proficiency with tools like Apache Spark, Airflow, or Databricks (preferred)Visualization skills using Streamlit, Tableau, or similar toolsKnowledge of data privacy, model governance, and financial regulatory requirementsStrong theoretical and practical understanding of Machine and Deep Learning principlesNLP expertise covering text processing, tokenization, language models, and advanced techniquesComputer Vision fundamentals for document image analysis and chart data extractionHands-on experience with ML libraries : NumPy, PyTorch, HuggingFace, OpenCV, scikit-learn, spaCy, NLTKExperience with vector databases, good understanding of LLMs and Prompt Engineering, and knowledge of frameworks like LangChainAPI development using Flask, FastAPI, Django or similar frameworksGood communication skills for explaining complex concepts to diverse audiencesSelf-direction and organizational abilities to manage multiple concurrent projectsPassion for continuous learning in the rapidly evolving ML / DL landscapeOpen-source contributions or maintenance experience (preferred)Why Join 73Strings
As part of our team, you'll work at the forefront of AI innovation in financial technology, solving challenging problems that transform how financial professionals conduct valuations and investment analysis. You'll build systems that extract critical data from diverse sources, design intelligent agents that interact with structured financial data, and create tools that derive competitor insights from web data and third-party platforms. If you're passionate about using machine learning to revolutionize financial workflows and enable more accurate, data-driven investment decisions, we want to hear from you.
Department Technology Locations Paris