Research Engineer

Accountabilities: Lead the development and deployment of efficient, adaptive machine learning systems in real production environments. Design and implement data strategies and pipelines that enable production signals to feed back into model retraining and fine-tuning. Own the implementation of data products, taking ideas from research and experimentation through to reliable production systems. Develop solutions to novel challenges involving data collection, interaction, evaluation, and continual model adaptation. Contribute to applied research initiatives while ensuring research concepts can translate into practical, scalable products. Work closely with technical and product stakeholders to shape research priorities and align engineering decisions with broader product goals. Apply creativity, technical judgment, and strong execution to solve complex machine learning and systems-level challenges. Help advance approaches to efficient intelligence, continual adaptation, and real-time model evolution. Requirements Bachelor’s degree in Computer Science, Machine Learning, or a related technical field. 3–4 years of professional experience in machine learning, applied research, or systems-level engineering for artificial intelligence. Demonstrated experience closing the loop between production signals and model retraining or fine-tuning. Practical knowledge of online learning, reinforcement learning, efficient ML architectures, or related approaches to adaptive AI. Strong software engineering capabilities and professional experience with Python. Previous exposure to observability and infrastructure tools such as OpenTelemetry, Docker, or Grafana. Ability to translate research concepts and technical experimentation into robust, production-ready implementations. Excellent communication skills, with the ability to connect technical decisions to high-level business and product objectives. Strong sense of ownership, curiosity, initiative, and a bias toward action. Comfortable working in an environment where requirements evolve, problems are novel, and experimentation is encouraged. Collaborative mindset and willingness to challenge conventional approaches with thoughtful, ambitious ideas. Benefits Flexible remote work within a globally distributed team, with opportunities for in-person collaboration and team offsites. Annual travel stipend through the Adaption Passport , supporting travel to a country you have never visited. Weekly lunch stipend for take-out or grocery delivery. Comprehensive medical benefits. Generous paid time off. Opportunity to work closely with a founding team on cutting-edge applied ML research and products. High level of ownership and direct impact on the development of continuously adapting AI systems. Global working environment that encourages collaboration, curiosity, experimentation, and bold ideas.