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About The Company
Bumble is a pioneering technology company dedicated to transforming the online dating landscape through innovative solutions powered by artificial intelligence. With a focus on fostering genuine connections and enhancing user experiences, Bumble continuously pushes the boundaries of what is possible in the realm of digital matchmaking. Our commitment to innovation, inclusivity, and user-centric design has established us as a leader in the industry. We strive to create a safe, engaging, and empowering environment for our users worldwide, leveraging cutting-edge AI technologies to redefine how people connect and form meaningful relationships online.
About The Role
We are seeking a highly skilled and innovative Machine Learning Engineer to join our dynamic team at Bumble. In this role, you will be instrumental in developing next-generation AI-driven features that enhance our platform's capabilities. You will work closely with cross-functional teams to design, implement, and optimize machine learning models that improve user engagement and experience. As a key member of our team, you will contribute to the technical evolution of our products by integrating advanced generative AI solutions, ensuring scalability, performance, and fairness. Your expertise will help shape the future of online dating, making connections more meaningful and intuitive.
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Qualifications
- Advanced degree in Computer Science, Mathematics, or a related quantitative discipline
- Hands-on experience deploying machine learning models at scale in production environments
- Proficiency in Python programming, with a focus on production-quality code
- Experience with ML frameworks such as PyTorch or TensorFlow
- Knowledge of modern LLM deployment frameworks and libraries, including HuggingFace TGI, VLLM, TensorRT-LLM, or similar
- Understanding of machine learning lifecycle processes and tools: CI/CD, version control (git), testing frameworks, MLOps, agile methodologies, monitoring, and alerting
- Experience working with Docker and containerized applications
- Proficiency in deploying high-load ML applications on container orchestrators like Kubernetes (bare-metal, GKE, EKS)
- Knowledge of GPU-powered workloads, NVIDIA drivers, and container runtimes
- Strong communication skills and ability to collaborate effectively with technical and non-technical stakeholders
- A genuine passion for AI and ML, with a thoughtful approach to AI fairness, accountability, and transparency
Responsibilities
- Collaborate within a small, agile team to develop innovative AI-powered features for our applications
- Contribute to the technical design, development, and deployment of generative AI models
- Work closely with cross-functional teams to identify user needs and translate them into technical solutions
- Optimize AI and ML solutions for performance, scalability, and reliability in production environments
- Mentor and coach team members on best practices in ML engineering and deployment
- Stay current with the latest advancements in AI and machine learning to drive continuous innovation
- Partner with the MLOps team to implement robust deployment pipelines and monitoring systems
- Ensure AI solutions adhere to ethical standards, fairness, and transparency guidelines
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Benefits
- Competitive salary and performance-based bonuses
- Comprehensive health, dental, and vision insurance plans
- Flexible work hours and remote work opportunities
- Generous paid time off and holiday leave
- Professional development programs and continuous learning opportunities
- Collaborative and inclusive work environment
- Access to cutting-edge AI tools and resources
- Wellness programs and employee assistance initiatives
Equal Opportunity
Bumble is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, ethnicity, gender, sexual orientation, age, disability, religion, or any other protected status. We believe that diverse perspectives and backgrounds foster innovation and help us better serve our global community.
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