Senior Machine Learning Engineer

This position is exclusively open to candidates based in Latin America.
About the Company:
The firm was formed in 2016, born out of a vision and desire to innovate the private equity industry and to capitalize on the significant financial technology opportunity. We are a specialist investment firm that invests in software, information & investment services companies providing mission-critical products and services across five core sub-sectors: Banking & Payments, Capital Markets, Data & Analytics, Insurance, and Investment Management. We seek growth equity and buyout opportunities in North America and Europe. We are a sector-specialist private equity firm with expertise, connectivity, and capabilities to create long-term value in financial technology businesses. By applying extensive Investing, Operating, and Innovating capabilities we seek to enable management teams to accelerate growth, achieve operational excellence, and innovate in a dynamic sector. Our integrated approach combines Investors (Capital and Ventures), Operators (Industry Partners) and Innovators (Create). Each of these divisions works in partnership across the workflow of the business: originating deals, performing diligence, underwriting the deals, executing the value creation plans, and ultimately exiting the deals.
We leverage our proprietary expertise in financial technology to identify, unlock, and accelerate value for our portfolio companies and partners. We believe deeply in the power of technology to transform businesses and industries. Utilizing our broad market connectivity and market-leading technology capabilities we aim to be at the forefront of innovation as it emerges, delivering new capabilities into the hands of our portfolio and partners. Our innovation and value creation engine is structured across three disciplines:Portfolio Services – Experts in executing due diligence, value creation planning, and portfolio value creation execution.Propositions – Driving innovation for our portfolio and partners. Product – Building new technology assets and platforms that underpin our value creation and innovation activities.
About the Role:We are seeking a Machine Learning Engineer with full-stack development capabilities to lead the creation of our Financial Advisor Co-pilot. This role is at the forefront of our AI-driven solutions, crafting the predictive models that will underpin the next generation of wealth management products. The ideal candidate is not only an expert in machine learning but also possesses a robust set of full-stack development skills to build and deploy scalable applications.

Responsabilities

• Lead the end-to-end development and deployment of predictive models for wealth management solutions, from database to user interface.
• Design, build, and implement AI Co-Pilots, specifically tailored for the Wealth and Asset Management industry.
• Partner with the Director of Artificial Intelligence to conceptualize and execute a comprehensive strategy for integrating AI across business units.
• Rapidly prototype new algorithms and models, and transition from prototype to production environment, ensuring scalability and robustness
• Develop full-stack solutions, including database schema design, back-end logic, and front-end presentation.
• Measure and optimize the performance of both machine learning models and the full-stack applications, ensuring they align with business objectives.
• Collaborate with cross-functional teams to ensure that AI solutions enhance user experience and add significant business value.
• Act as a technical leader within the team, providing guidance and mentorship to other engineers.

Qualifications

• Minimum of 4+ years of experience in machine learning and full-stack development.
• Demonstrated experience building and deploying machine learning models, as well as constructing and maintaining full-stack applications.
• Proven track record of building and deploying machine learning models in a business context.
• Proficient in utilizing a range of machine learning libraries and frameworks (such as TensorFlow, PyTorch, Scikit-learn, Keras, etc.) to build, train, and deploy models efficiently.
• Proficiency with the LangChain framework, including experience in building applications with complex LLM integrations, using retrieval-augmented generation for contextual search, and adeptness in prompt engineering for effective human-AI interaction
• Strong engineering skills, including proficiency in Python.
• Familiarity with cloud platforms (AWS, GCP, Azure) and understanding of containerization and orchestration tools (Docker, Kubernetes).
• Ability to rapidly prototype and innovate, while maintaining a focus on scalable solutions.
• Strong problem-solving skills and the ability to learn on the job, staying ahead of the latest industry trends.
• Self-starter, capable of learning on the job and adapting to new challenges.