• Design, build, and ship production new machine learning models that power core product features on the Zillow app, website, and email/push notifications. • Re-architect our core home ranking and recommendation systems to support advanced neural networks and dramatically accelerate the pace of experimentation across surfaces. • Own the full lifecycle of your models, from offline experimentation and prototyping with massive datasets to online deployment, A/B testing, and performance monitoring. • Pioneer the application of cutting-edge deep learning and large language models (LLMs) to improve our home shopping experience. • Develop new AI components that optimize how we display and when we recommend homes, ensuring we connect shoppers with the right content on the right properties at the right time. • Collaborate in a cross-functional group of engineers, applied scientists, product managers, and designers to define, execute, and iterate on the team's strategic roadmap. • Contribute to the team's engineering excellence by improving our machine learning infrastructure, development standards, and shared tooling. • Act as a key technical voice, mentoring other engineers and helping to shape the long-term vision for artificial intelligence in the home shopping experience.

• Design, build, and deploy machine learning models that improve the accuracy and quality of design imports at scale • Work closely with engineers to integrate ML systems into high-performance backend and rendering pipelines • Define data strategies — including data collection, labeling approaches, and evaluation frameworks — to continuously improve model performance • Take a new perspective on existing import solutions and apply analytical thinking to solve complex, ambiguous problems • Contribute to architectural decisions that impact the broader Editing Platform ecosystem • Champion experimentation, monitoring, and model observability best practices • Collaborate across teams to identify opportunities where ML can unlock step-change improvements in user experience

Entefy’s Machine Learning Engineer is a highly visible position internally and externally. This is where your deep experience and great insights intersect with an amazing opportunity to shape the future of communication and digital interaction. Skills and Experience: We’re not looking for “good.” Entefy is on a mission for best. The success of this mission depends on its team members to be creatively analytical, insatiably curious, and absolutely fearless in tackling big challenges. Requirements

About us: Let’s be real, AI isn’t magic; Legion was built to move beyond AI hype—delivering secure, reliable systems that work alongside the people tackling the world’s most critical challenges. Born from a Department of Defense partnership and trusted by leaders across government and enterprise, Legion embeds intelligence inside complex systems, unlocking data, accelerating human workflows, and strengthening mission-critical systems. We don’t replace workflows—we optimize them, ensuring quality, efficiency, and reliability inside the platforms our partners already use. With world-class collaborators like Palantir, Nvidia, HPE, and Oracle, we’re building intelligent infrastructure that enhances human capability and drives impact at the edge and across a range of enterprises. We’re looking for bold thinkers and doers to join us in shaping the future of AI that’s secure, grounded, and built to work. Job Summary: Are you an experienced Applied Machine Learning Engineer who thrives in a fast-paced, collaborative team? We seek a highly skilled Senior Applied Machine Learning Engineer to join our Applied ML team. In this role, you will leverage your expertise in AI/ML engineering to design, develop, and deploy innovative machine learning and algorithmic solutions. If you are adept at building models that solve hard problems, we encourage you to apply. You will collaborate closely with platform engineers and product partners, bringing a strong product orientation to your ML work. Responsibilities: Lead the development of machine learning models and data-driven algorithms for high impact projects Collaborate with product and platform teams to own ML solutions end-to-end Understand the runtime complexity of algorithms and the cost to run ML models at a production scale Clearly communicate modeling decisions, tradeoffs, and limitations to technical and non-technical stakeholders Build, deliver, and maintain enterprise products, ensuring they meet high-quality standards while shipping fast Take ownership of your work, from design to implementation and maintenance, and drive projects to successful completion Support production systems, handling debugging challenges in distributed systems to ensure reliability and uptime Adapt quickly, bringing in latest developments in AI and machine learning, and proactively apply this knowledge to drive innovation within the company Required Skills and Qualifications: Preferred Qualifications: Start-up experience or comfort in 0→1 product environments. Familiarity with Kubernetes is a plus. Experience integrating machine learning models and data driven algorithms into larger system architectures. Compensation Information $205,000 — $260,000 USD