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Software Engineer, Applied ML - 2025 at Brave. . Location: London, England. 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 Brave's mission to revolutionize web browsing through AI. We're looking for an experienced ML Engineer to build next-generation features that serve nearly 100 million users worldwide. You'll 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. . . 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. . Design, optimize, and maintain ML inference pipelines for browser-integrated AI features, with focus on reducing deployment costs and improving model performance. . 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. . Generate synthetic data for training data augmentation and model evaluation. . Collaborate with browser engineering teams to seamlessly integrate AI capabilities into core product features while maintaining performance and privacy standards. . 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. . Implement and optimize model serving infrastructure using frameworks like vLLM, ONNX Runtime, and Nvidia Triton to achieve production-scale performance requirements. . Collaborate with DevOps teams on MLOps infrastructure including model monitoring, load testing, caching optimization, and automated CI/CD pipelines for model deployments. . Contribute to privacy-preserving ML approaches and on-device model implementations that align with Brave's privacy-first mission. . . Required Qualifications. . . 2 to 5 years of experience optimizing and deploying ML models in production environments. . Strong software engineering background with production experience. . Extensive experience with PyTorch or other modern ML frameworks. . Experience training custom models from scratch. . Experience with model optimization and inference frameworks (e.g., vLLM, ONNX Runtime, Nvidia Triton). . Familiarity with MLOps practices & Kubernetes and ability to collaborate with DevOps teams on model monitoring, load testing, and CI/CD pipelines. . Experience shipping ML-powered features or systems (consumer applications preferred). . . Preferred Qualifications. . . Master's degree in Computer Science, Machine Learning, or related field. . Familiarity with LLM serving frameworks (vLLM, TGI, Ray Serve) and GPU optimization. . Experience with embeddings, vector databases, semantic search implementations, model training workflows, and data pipeline development. . Experience integrating LLMs with tool calling/MCP. . Knowledge of privacy-preserving ML techniques and on-device model deployment. . Previous work on cost optimization and performance tuning of ML systems at scale. . . What We're Looking For. . . Deep curiosity about emerging AI models and their practical applications. . Strong problem-solving skills with ability to work in ambiguous environments. . Excellence in cross-functional collaboration and technical communication. . Drive to make AI technology more accessible through the browser. . Pragmatic approach to balancing innovation with shipping products. . . What We Offer. . . Opportunity to shape the future of AI-powered browsing experiences. . Work with cutting-edge technology and state-of-the-art ML tools. . Competitive compensation with room for growth. . Great international exposure and team atmosphere. . Flexible work location with preference for London office. . . While we prefer candidates who can work from our London office, we're 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.. .  . .