Engineering Manager, Applied AI & Machine Learning Engineering

At SPD Technology, we bring together a team of like-minded people who are driven by the desire to bring value through their work, united in their commitment to high performance and delivering custom, cutting-edge tech solutions that drive clients’ growth. We empower our people with a culture of excellence and enable them with the opportunity to uphold their accountability to contribute on each level. We value humanity and collaboration, encourage professional and personal growth, and foster a supportive and flexible work environment where everyone’s contribution is welcomed. And now we are looking for a Engineering Manager, Applied AI & Machine Learning Engineering to join us as part of our team. About Role PitchBook — a platform for investment professionals. Our software provides access to data and the analytical tools to get answers fast and discover promising opportunities. Uncovers actionable insights and trends hidden within the financial data of more than three million companies. Users all over the world include large corporations, start-ups, venture capital and private equity firms, investment banks, and many others. As an Engineering Manager, AI/ML, you will support a cross-functional team of MLE and MLOps engineers working across several AI/ML initiatives. Your primary focus will be resource planning, execution, and people management. You will work closely with project leads, technical leads, functional managers, and product partners to ensure projects are appropriately staffed, plans are realistic, risks are visible, and teams can deliver effectively. You will manage capacity and resource allocation across multiple projects, help coordinate dependencies and priorities, and provide stakeholders with a clear view of delivery progress. Project and technical leads will continue to own product direction and technical decisions. You will also support the career growth and performance of team members. This includes gathering feedback, coaching employees, creating development plans, and contributing to performance, promotion, and compensation reviews. You should have enough AI/ML experience to understand the work, communicate effectively with engineers, and identify technical delivery risks. However, this is not expected to be a hands-on engineering or architecture role. Our Tech Stack & Focus Areas Generative AI & LLMs: Develop and maintain LLM-based solutions for generative features. Classic ML Models: Develop and maintain predictive and classification models for financial data Vector Databases: Implementing efficient storage and retrieval systems for high-dimensional data embeddings. Embeddings: Developing hybrid models to extract insights from diverse data sources. High-Volume Data Management: Engineering systems capable of handling massive, real-time data streams. Work Environment Flexible schedule with participation in team ceremonies and cross-functional collaboration. Time zone: Europe/Kyiv. As a qualified expert,…