Senior Machine Learning Infrastructure Engineer, Social

<p><strong>About Mozilla</strong></p> <p>Mozilla Corporation is the non-profit-backed technology company behind pioneering brands like Firefox, the privacy-minded web browser, and Pocket, a service for keeping up with the best articles online. More than 225 million people around the world use its products each month.</p> <p>Along with 60,000+ volunteer contributors and collaborators all over the world, Mozilla Corporation’s staff are driven by our mission to ensure the Internet is a global public resource, open and accessible to all. We design, build and distribute open-source software that enables people to enjoy the internet on their terms.</p> <p><strong>The opportunity and team</strong></p> <p>At Mozilla Social, we are focused on connecting people to the power, possibility &amp; magic of the web in a safe and trusted way. Mozilla Social’s vision is to develop an integrated platform that empowers users through seamless communication, content discovery, and, enabling them to stay up-to-date, explore new perspectives, and engage within a safe and enriching experience.</p> <p>MozSocial is a part of the Mozilla Corporation. We are committed to an internet that elevates critical thinking, reasoned argument, shared knowledge, and verifiable facts. As part of our Machine Learning team, you’ll be responsible for helping ensure our ability to support high-quality content on the web. This role is fundamental to Mozilla Social’s success.</p> <p>Are you excited about the role of content and communication platforms enriching human lives through learning and teaching, discussion and open unbiased conversations? Do you want to build and deploy machine learning models for a massive audience? </p> <p>We’re looking for a passionate, driven, and experienced engineer to help us deliver world-class product experiences driven by machine learning across the product line.  We are looking for a Machine Learning Infrastructure Engineer to help design and deploy innovative ML solutions at scale.<br/></p> <p>Come work with us and make a huge impact on promoting high-quality content and respectful conversation on a social platform!</p> <p><strong>What you’ll do:</strong></p> <ul> <li>Participate in building and deploying APIs for large-scale recommendation and search algorithms and ML systems.</li> <li>Develop and maintain scalable machine learning workflows to process large amounts of data and train ML classification and recommendation models from large datasets. This includes integrating a variety of tools such as data pipelines, feature stores, and vector databases.</li> <li>Deploy scalable serving infrastructure to serve model inference results and monitor quality. Improve performance under load by implementing model quantization, adaptive inference and other techniques.</li> <li>Drive the development of innovative machine learning products, collaborating cross functionally with infrastructure team, full stack engineering and design.</li> <li>Be hands on - directly solving some of the big, challenging product problems at the intersection of systems engineering and AI, serving hundreds of communities and millions of customers.  </li> </ul> <p><strong>What you bring: </strong></p> <ul> <li>Demonstrable experience deploying production-ready machine learning models using cloud infrastructure including CPU and GPU with Docker</li> <li>Demonstrable experience with monitoring and alerting for machine learning pipelines and model metrics for offline evaluation and production success.</li> <li>At least 5 years of experience supporting machine learning environments with ability to show activity and output in the space during that time.</li> <li>Hands-on experience with cloud-based infrastructure and related tools such kubernetes, Argo, CI-CD tools, and Infrastructure as code.</li> <li>Familiar with concepts like firewalls, encryption, VPNs, and secure data transfer</li> <li>Knowledge of how to optimize models for production usage, including considerations for scalability, latency, and resources</li> <li>Experience in building and deploying machine learning frameworks such as TensorFlow / PyTorch, NumPy and scikit-learn in a distributed environment using CI/CD</li> </ul> <p><strong>Bonus points:</strong></p> <ul> <li>Experience with training and deployment of LLMs such as LLaMa using GPUs</li> <li>Experience with GCP cloud provider and AI frameworks such as Vertex AI</li> <li>Experience in using popular MLOps frameworks like KubeFlow, MLFlow, Ray and others</li> <li>Experience with online experimentation (e.g. a/b testing)</li> <li>Experience with data analysis tools such as Big Query, DBT and Spark.</li> <li>AI related degree or training certificate completed in the last 12 months.</li> <li>Bachelor's or Master's degree in Computer Science, Mathematics, or a related field. PhD is a plus.</li> <li>Awareness or experience with trust, fairness, or privacy-preserving machine learning</li> </ul> <p>Our team requires skills in a variety of doma