Define and lead the technical strategy for AI and Machine Learning systems that power recommendations, ranking, and personalization across Bumble products, delivering measurable improvements in user engagement and safety
Design, develop, and deploy production-grade models using modern ML frameworks such as PyTorch , ensuring scalability and reliability in high-traffic environments
Build and deploy production AI Agents using raw and fine-tuned foundational Large Language Models (LLMs), along with sub-agents, tools, and MCP integrations
Architect end-to-end ML pipelines, integrating data processing (e.g. Spark, Airflow) with model training, evaluation, and deployment workflows
Drive experimentation frameworks, including A/B testing and offline evaluation, to continuously improve model performance and product outcomes
Partner cross-functionally with Product, Engineering, and Data leadership to translate business challenges into impactful ML solutions, collaborating with purpose and influencing at senior levels
Mentor and elevate senior individual contributors, fostering a culture of Excellence, Curiosity, and continuous learning across the ML community
Take ownership of complex, ambiguous problem spaces, seeing initiatives through from insight to impact while adapting approaches with an agile mindset
Champion responsible AI practices, ensuring fairness, transparency, and user safety are embedded into all machine learning systems

Typically requires 10–15 years of experience, though we welcome candidates with alternative backgrounds that demonstrate equivalent skills.
Deep expertise in machine learning, with hands-on experience building and deploying large-scale systems in production environments
Strong proficiency in Python and at least one major ML framework (e.g. PyTorch, TensorFlow), with experience in areas such as recommendation systems, ranking models, or NLP
Expertise in prompting and fine-tuning Large Language Models (LLMs) and building production AI Agents
Proven experience designing scalable data and ML pipelines using tools such as Spark, Airflow, or similar distributed systems
Demonstrated ability to operate as a senior individual contributor, influencing technical strategy and decision-making without direct authority
Experience partnering effectively across functions, collaborating with purpose and taking ownership of outcomes in complex organisational environments
A track record of mentoring and uplifting others, role modelling Respect and Excellence while building inclusive, high-performing teams
Strong AI fluency, with the ability to independently design, evaluate, and optimise ML systems, and guide others in the responsible and effective application of AI

Principal Machine Learning Engineer

Key skills