<div class="content-intro"><p><em>At Klaviyo, we value the unique backgrounds, experiences and perspectives each Klaviyo (we call ourselves Klaviyos) brings to our workplace each and every day. We believe everyone deserves a fair shot at success and appreciate the experiences each person brings beyond the traditional job requirements. If you’re a close but not exact match with the description, we hope you’ll still consider applying. Want to learn more about life at Klaviyo? Visit <a class="_ymio1r31 _ypr0glyw _zcxs1o36 _mizu194a _1ah3dkaa _ra3xnqa1 _128mdkaa _1cvmnqa1 _4davt94y _4bfu18uv _1hms8stv _ajmmnqa1 _vchhusvi _kqswh2mm _ect4ttxp _syaz13af _1a3b18uv _4fpr8stv _5goinqa1 _f8pj13af _9oik18uv _1bnxglyw _jf4cnqa1 _30l313af _1nrm18uv _c2waglyw _1iohnqa1 _9h8h12zz _10531ra0 _1ien1ra0 _n0fx1ra0 _1vhv17z1" href="http://klaviyo.com/careers" data-renderer-mark="true">klaviyo.com/careers</a> to see how we empower creators to own their own destiny.</em></p></div><p>At Klaviyo, we believe the future of software lies not in productivity tools for human users but in software that can run and optimize itself based on outcome or reward metrics. We’ve built the infrastructure and application that serve as the interface between businesses and consumers. We now have over 167,000 customers, billions of consumer profiles, and hundreds of billions of customer messages and follow-on conversion data. We are building state-of-the-art AI and machine learning technologies at Klaviyo to power Composer, as well as personalization products such as smart send time, audience optimization and product recommendations.</p> <p>As a <strong>Senior Machine Learning Platform Engineer</strong>, you will help build the core platforms, tools, and infrastructure that ML and AI engineers rely on to create advanced agents and models powering Klaviyo’s products. You will drive key technical initiatives for <strong>training and deploying models</strong>, <strong>unifying and standardizing feature data</strong>, and <strong>scaling systems</strong> that must operate reliably at Klaviyo’s data and traffic scale.</p> <p>This is a <strong>backend-heavy, hands-on technical individual contributor</strong> role. You will lead technical execution, conduct code and design reviews, author high-impact code for critical system paths, and collaborate closely with product, ML, data science, and infrastructure partners to deliver durable, high-leverage platforms that accelerate AI development across Klaviyo.</p> <p><em>This role is based in Boston.</em></p> <p><strong>How You’ll Make an Impact</strong></p> <p> </p> <ul> <li>Enable AI / ML teams across Klaviyo to ship new models and ML-powered features faster, more safely, and more reliably.</li> <li>Evolve our ML and LLM platform architecture so teams can build, evaluate, and operate production ML systems with consistent patterns and best practices.</li> <li>Improve reliability, observability, and cost efficiency of ML training, inference, and other ML workloads that serve features like smart send time, audience optimization and product recommendations.</li> <li>Raise the bar on engineering and operational excellence for systems that support 167K+ customers and billions of events.</li> <li>Architect and scale systems supporting feature storage and real-time retrieval for training and inference datasets</li> </ul> <p> </p> <p><strong>What You’ll Do</strong></p> <ul> <li>Work closely with AI & ML application teams to design seamless workflows for continuous model training, inference, and monitoring</li> <li>Lead technical execution, conduct code and design reviews, and author high-impact code for critical system paths.</li> <li>Mentor engineers across the organization, promoting engineering excellence, best practices, and strong design standards.</li> <li>Drive architectural design and technical direction for core components of the ML and Feature platforms.</li> <li>Partner with product and engineering leaders to define the ML Platform roadmap.</li> </ul> <p>Learn more about the team’s work in our blogs on <a href="https://klaviyo.tech/how-klaviyo-built-an-unbreakable-system-for-running-distributed-ml-workloads-f6ea35567458">Ray Jobs</a> & <a href="https://klaviyo.tech/ray-data-train-tune-at-klaviyo-bca9f14abf21">Ray Tune</a>.</p> <p><strong>Who You Are</strong></p> <p><em>We encourage candidates to apply even if they do not meet all the qualifications listed. ML Platform and MLOps are rapidly evolving spaces and we are all constantly learning.</em></p> <ul> <li>7+ years of experience as a software engineer, ML platform engineer, or similar, building backend or distributed systems.</li> <li>Demonstrated experience designing and launching AI/ML systems in production at scale</li> <li>Strong proficiency in Python (or a similar backend language such as Go, Java, or Scala).</li> <li>Experience with cloud infrastructure and platform fundamentals (AWS, kubernetes):</li> <li>Familiarity with data-intensive systems: streaming or batch processing, data modeling, and designing systems with large-scale data in mind (spark, ray-data).</li> <li>Comfortable collaborating with cross-functional technical partners (ML, product, infra, security).</li> <li>Strong communication skills and a track record of driving technical excellence across teams.</li> </ul> <p><strong>What to Expect in Your First 90 Days</strong></p&