Remote / Hybrid preferred About Brave Brave is on a mission to protect the human right to privacy online. We’ve built a free web browser that blocks creepy ads and trackers by default, a private search engine with a truly independent index, a browser-native crypto wallet, and a private ad network platform that directly rewards you for your attention. And we’re just getting started. 90 million people have switched to Brave for a faster, more private web. Millions more switch every month. Summary Join Braves mission to revolutionize web browsing through AI. Were looking for an experienced ML Engineer to build next-generation features that serve nearly 100 million users worldwide. Youll work with state-of-the-art language models, collaborating across teams to ship innovative AI capabilities that make the browser smarter and more capable—all while maintaining our privacy-first principles. Core Responsibilities <ul> <li>Evaluate, integrate, and deploy state-of-the-art language models for Leo and other browser AI capabilities, including both cloud-based and on-device deployment scenarios</li> <li>Design, optimize, and maintain ML inference pipelines for browser-integrated AI features, with focus on reducing deployment costs and improving model performance</li> <li>Develop and train custom ML models for browser-specific use cases such as content classification and search optimization using techniques like LoRA and DPO, including distributed training setups</li> <li>Generate synthetic data for training data augmentation and model evaluation</li> <li>Collaborate with browser engineering teams to seamlessly integrate AI capabilities into core product features while maintaining performance and privacy standards</li> <li>Collaborate with product and design teams to define, prototype, and ship new AI-powered features including text-to-speech, image generation, and enhanced tool calling capabilities</li> <li>Implement and optimize model serving infrastructure using frameworks like vLLM, ONNX Runtime, and Nvidia Triton to achieve production-scale performance requirements</li> <li>Collaborate with DevOps teams on MLOps infrastructure including model monitoring, load testing, caching optimization, and automated CI/CD pipelines for model deployments</li> <li>Contribute to privacy-preserving ML approaches and on-device model implementations that align with Braves privacy-first mission</li> </ul> Required Qualifications <ul> <li>2 to 5 years of experience optimizing and deploying ML models in production environments</li> <li>Strong software engineering background with production experience</li> <li>Extensive experience with PyTorch or other modern ML frameworks</li> <li>Experience training custom models from scratch</li> <li>Experience with model optimization and inference frameworks (e.g., vLLM, ONNX Runtime, Nvidia Triton)</li> <li>Familiarity with MLOps practices &amp; Kubernetes and ability to collaborate with DevOps teams on model monitoring, load testing, and CI/CD pipelines</li> <li>Experience shipping ML-powered features or systems (consumer applications preferred)</li> </ul> Preferred Qualifications <ul> <li>Masters degree in Computer Science, Machine Learning, or related field</li> <li>Familiarity with LLM serving frameworks (vLLM, TGI, Ray Serve) and GPU optimization</li> <li>Experience with embeddings, vector databases, semantic search implementations, model training workflows, and data pipeline development</li> <li>Experience integrating LLMs with tool calling/MCP</li> <li>Knowledge of privacy-preserving ML techniques and on-device model deployment</li> <li>Previous work on cost optimization and performance tuning of ML systems at scale</li> </ul> What Were Looking For <ul> <li>Deep curiosity about emerging AI models and their practical applications</li> <li>Strong problem-solving skills with ability to work in ambiguous environments</li> <li>Excellence in cross-functional collaboration and technical communication</li> <li>Drive to make AI technology more accessible through the browser</li> <li>Pragmatic approach to balancing innovation with shipping products</li> </ul> What We Offer <ul> <li>Opportunity to shape the future of AI-powered browsing experiences</li> <li>Work with cutting-edge technology and state-of-the-art ML tools</li> <li>Competitive compensation with room for growth</li> <li>Great international exposure and team atmosphere</li> <li>Flexible work location with preference for London office</li> </ul> While we prefer candidates who can work from our London office, were open to remote candidates in compatible time zones. We offer flexible working arrangements to support a healthy work-life balance. Compensation £100,000 to £125,000 (USD$125,000 to USD$155,000) - Depends on Location, Market Rate and Experience.