Senior Machine Learning Engineer

<b>The Opportunity:</b>Ready to help shape the future of SEO with cutting-edge ML/AI? We're looking for an experienced Senior Machine Learning Engineer to join our team at Moz, where you'll build and deploy ML/AI solutions that empower marketers worldwide.In this role, you'll get to flex your ML muscles across a variety of exciting challenges – from traditional ML models that predict search trends to LLM applications that help our users create better content. You'll work alongside our ML Lead and collaborate with teams across Moz to ship features that make a real difference in how people approach SEO and digital marketing. Whether you're optimizing ranking models, building intelligent content recommendations, or experimenting with the latest LLM techniques, you'll have the opportunity to work on meaningful problems at scale. We believe in doing ML the right way – with solid engineering practices, thoughtful evaluation, and a focus on delivering genuine value to our users. If you're passionate about machine learning, love solving complex problems, and want to work on products that help millions of marketers succeed online, we'd love to hear from you! <b>Key Responsibilities:</b><b>Model Development &amp; Evaluation</b><ul><li>Implement and optimize LLM-based features including prompt engineering, fine-tuning, and RAG systems</li><li>Design, develop, and train machine learning models for various business applications (classification, regression, NLP)</li><li>Conduct rigorous model evaluation using appropriate metrics and cross-validation strategies</li><li>Develop evaluation pipelines for both traditional ML models and LLM applications</li><li>Create reproducible experimentation frameworks for model iteration and improvement</li><li>Build ensemble methods and optimize model architectures for performance/accuracy trade-offs</li></ul><b>ML Systems &amp; Infrastructure</b><ul><li>Deploy ML infrastructure on AWS (SageMaker, Bedrock, EC2)</li><li>Develop cost-effective solutions for both traditional models and LLMs</li><li>Use Docker and Terraform to manage ML environments</li><li>Build real-time and batch inference systems for ML models</li><li>Create data pipelines and feature stores for model training</li><li>Set up vector databases and RAG systems for LLM applications</li><li>Implement monitoring and alerts for models in production</li><li>Manage both traditional ML workloads and LLM API integrations</li><li>Stay current with ML advancements, especially in LLMs</li></ul><b>Team Collaboration</b><ul><li>Collaborate with engineering teams to integrate ML features into products</li><li>Participate in code reviews ensuring high-quality, maintainable ML code</li><li>Contribute to technical documentation and knowledge sharing</li><li>Support other engineers in understanding and using ML systems</li><li>Partner with product teams to scope and deliver ML features</li></ul> <b>Job Qualifications:</b><b>Technical Skills</b><ul><li><b>6+ years</b> of experience in machine learning engineering or data science</li><li><b>3+ years</b> of production Python development with experience in ML frameworks (PyTorch, TensorFlow, Scikit-learn, XGBoost)</li><li>Experience in building RESTful APIs and microservices</li><li>Experience with AWS services including:</li><ul><li>SageMaker for model training and deployment</li><li>S3, DynamoDB for data storage</li><li>Experience with Bedrock or similar LLM services</li></ul><li>Experience with Docker and containerization</li><li>Experience with the full ML lifecycle: problem framing, data analysis, model development, evaluation, and deployment</li></ul><b>Engineering Skills</b><ul><li>Strong software engineering fundamentals and design patterns</li><li>Experience with version control (Git) and collaborative development</li><li>Understanding of distributed systems and scalability</li></ul><b>Bonus skills &amp; attributes </b><ul><li>Track record shipping ML products</li><li>PhD or other experience in a research environment</li><li>Deep experience in an applicable ML area. E.g. NLP, Deep learning, Bayesian methods, Reinforcement learning, clustering</li><li>Experience with Infrastructure as Code using Terraform or similar technology</li><li>Hands-on experience with LLM applications (prompt engineering, fine-tuning, RAG)</li></ul><p> </p><b>About Moz Group</b><b></b>The Moz Group, a subsidiary of Ziff Davis, Inc (NASDAQ: ZD), is a leading provider of marketing technology solutions primarily for small and medium-sized enterprises, consisting of a portfolio of brands across digital media and cloud services. Our SEO brands include Moz and STAT, Email Marketing brands include Campaigner, iContact, Kickbox, and SMTP, and finally our Communications brands are made up of Line2 and eVoice. The Moz Group is committed to building diverse teams where people of all identities and backgrounds are welcome, included, and respected. We work to help close the gender gap in tech, and to actively recruit people