Senior ML Engineer

About the role

<div class="content-intro"><p>At Anaplan, we are a team of innovators focused on optimizing business decision-making through our leading AI-infused scenario planning and analysis platform so our customers can outpace their competition and the market.</p> <p>What unites Anaplanners across teams and geographies is our collective commitment to our customers’ success and to our Winning Culture.</p> <p style="padding-left: 40px;">Our customers rank among the who’s who in the Fortune 50. Coca-Cola, LinkedIn, Adobe, LVMH and Bayer are just a few of the 2,400+ global companies who rely on our best-in-class platform.</p> <p style="padding-left: 40px;">Our Winning Culture is the engine that drives our teams of innovators. We champion diversity of thought and ideas, we behave like leaders regardless of title, we are committed to achieving ambitious goals, and we love celebrating<em> </em>our wins – big and small.</p> <p>Supported by operating principles of being strategy-led, <a href="https://www.anaplan.com/careers/">values</a>-based and disciplined in execution, you’ll be inspired, connected, developed and rewarded here. Everything that makes you unique is welcome; join us and let’s build what’s next - together!</p></div><p>You will join the Predictive Intelligence engineering team within Anaplan, building the backend services that power the ML Engine behind the Syrup platform and Anaplan’s forecasting solutions. The team is responsible for the production execution of forecasting and predictive models, the MLOps infrastructure supporting our data scientists, and the data processing services that deliver insights to enterprise customers. This role reports to the Director of Engineering for Predictive Intelligence and works closely with data scientists, ML engineers, and platform partners.</p> <p><strong>Your Impact</strong></p> <ul> <li>Design and implement scalable, fault-tolerant predictive intelligence services and features as a core contributor to the ML Engine backend.</li> <li>Lead the technical implementation of MLOps capabilities, including model training pipelines, deployment workflows, and runtime infrastructure for production ML.</li> <li>Partner with data scientists to productionize models and graduate experimental work into stable, observable production services.</li> <li>Drive the evolution of forecasting, scoring, and data processing services with a focus on performance, scalability, and cost efficiency.</li> <li>Take part in on-call rotations and own the operational health of high-availability production services, including incident response and post-incident improvements.</li> <li>Lead design reviews and code reviews, raising the quality bar across the team and mentoring mid-level and junior engineers.</li> <li>Identify and drive cross-cutting platform improvements that benefit multiple services and teams.</li> </ul> <p><strong>Your Qualifications</strong></p> <ul> <li>6+ years of professional software engineering experience building production backend services.</li> <li>Strong proficiency in Python, with a track record of writing performant, well-tested production code.</li> <li>Hands-on experience operating containerized services on Kubernetes in at least one major cloud (AWS, GCP, or Azure).</li> <li>Experience with data warehousing or analytics technologies such as Snowflake, Iceberg, Trino, or Postgres.</li> <li>Experience designing, deploying, and operating ML models in production, including familiarity with MLOps tooling such as MLflow.</li> <li>Demonstrated ability to work autonomously, take ownership of meaningful systems, and deliver against ambiguous requirements.</li> <li>Track record of being on-call for production services and contributing to operational excellence.</li> <li>Bachelor’s degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience.</li> </ul> <p><strong>Preferred Skills</strong></p> <ul> <li>Experience with gradient-boosted tree models, neural net

Skills