• Design, build, and deploy scalable machine learning models for OCR, document understanding, and voice processing • Research and implement algorithms for extracting structured information from unstructured documents and audio • Optimize and fine-tune models for real-world performance and reliability • Work alongside product, data, and engineering teams to integrate ML solutions into production workflows • Analyze model outputs, perform error analysis, and iterate quickly based on results and feedback • Document methodologies, experiments, and best practices

• Identify and formalize scenarios to be covered by the transactional antifraud system, especially in the AML domain. • Conduct research on cutting-edge ML models and techniques for fraud and anomaly detection in transactional data. • Build ML models (classic, graph-based, neural networks) and integrate them into the Fraud Protection platform. • Develop production-ready source code (primarily in Python; Go experience is a plus). • Document and present research findings.

Role Description We are looking for a Senior Machine Learning Engineer to join our AI Labs dynamic team! Our team comprises motivated individuals who collaborate to achieve remarkable feats daily. Together, we tackle challenges and emerge victorious, contributing to something monumental! If you thrive in a fast-paced collaborative environment, value and harness your teammates' opinions & expertise to deliver excellence, then come be a part of our team! - Develop and implement fast proof of concept (POCs) focused on LLM automations (prompt engineering, LLM based workflows and/or Agents for processing complex documents with legislation). - Implement solutions with multimodal VLMs (Vision-Language Models, such as GPT4o-vision or Mistral OCR) for OCR and to extract accurate data from tables. - Ensure quality in your delivery by following strictly CI/CD practices and ensuring proper integration of the features you implement. - Design prototypes of solutions for challenging business problems, with a focus on scalability and continuous improvement. - Collaborate with cross-functional teams to gather requirements and ensure solutions meet business needs. - Test, evaluate, and prompt engineer models to improve accuracy and performance of response systems. - Provide support for other technical duties, e.g. performing technical interviews for other ML and AI positions or collaborating in high level designs of AI/ML solutions during pre-sales. - Stay updated with advancements in AI and generative technologies to incorporate best practices into projects. - Document processes, learnings, and outcomes to support iterative development and knowledge sharing across teams. Qualifications - Software engineering degree or similar, with excellent software development skills. - Experience implementing LLM workflows and/or Agents using Langchain and OpenAI models. - Experience developing and deploying AI/ML solutions in AWS infrastructure. - Experience developing AI solutions in Python using OpenAI models and building scrappy UIs using Streamlit. - Excellent Prompt Engineering skills. - Previous experience working with Agile methodologies. - Experience working in multidisciplinary development teams. - Master level skills in Python and Git. - Excellent communication in English, both written and oral. - Proactivity and creativity. Requirements - Proven experience developing production-ready applications using voice-to-text and text-to-voice interfaces is a plus. - Experience in traditional NLP (before LLMs). - Experience using MLOps tools like MLFlow or other platforms for monitoring performance of AI/ML solutions. - Vibe coding experience in tools like v0.dev, generating baseline UIs for POCs. - Experience in any other fields of machine learning (deep learning, predictive models, recommendation engines, time series analysis, computer vision). - Experience doing live demos for customers. - Experience implementing good MLOps practices. - If you have implemented some degree of test driven development in your career for AI/ML solutions, let the team know! - Previous client facing positions. Benefits - 💵 Monthly USD Service Fee. - 🌴 20 business days of paid Agreed Time Off—Annual + 6 Local Holidays. - 🐣 Caregiver Time Off. - 💻 A dynamic remote work culture. You can work from anywhere! - 🚀 An entrepreneurial environment.

• Own the Problem Space: Translate ambiguous product concepts into concrete ML strategies • Architect for Healthcare: Fine-tune multi-modal generative models and orchestrate sophisticated AI agents • Establish Rigorous Evals: Define strict statistical and business metrics from day one • Ship & Monitor: Write production-grade Python and collaborate with engineering to deploy scalable solutions • Communicate & Execute: Operate with deep focus and autonomy, proactively align with stakeholders