Senior Machine Learning Engineer

<h3>📋 Description</h3> • Senior Machine Learning Engineer to join a cross-functional machine learning team shaping the future of Iterable's platform AI capabilities; architect and develop robust systems for feature engineering and large-scale model training—collaborating across teams and guiding technical direction. • Build end-to-end ML workflows and reusable, scalable ML infrastructure to accelerate experimentation and bring intelligent features to life. • Independently lead large-scale machine learning initiatives—delivering capabilities for scalable feature engineering, data processing, and model training on Databricks. • Design, build, and deploy machine learning models that enable partners to reach the right user with the right message at the right time. • Own the complete lifecycle of ML platform features: requirements gathering, architecture, implementation, deployment, and post-launch support. • Mentor colleagues through code reviews and knowledge sharing to grow engineering rigor. <h3>🎯 Requirements</h3> • 5+ years of experience in machine learning engineering, data infrastructure, or platform engineering, preferably in a SaaS environment. • Demonstrate a strong track record leading multi-stakeholder projects that deliver platform features, scalable ML tooling, or end-to-end training systems. • Proficiency with Python (with a preference for experience in distributed data processing environments like Databricks, Spark, or similar platforms). • Hands-on experience with large-scale data pipelines, distributed systems, and cloud data storage (Databricks Delta, Spark, Kafka, Postgres, etc.). • Exhibit a product-minded approach: comfortable partnering with product managers and data practitioners to balance trade-offs across usability, scalability, and complexity. • Possess curiosity and adaptability to master new ML and data technologies, frameworks, and best practices. • Communicate and collaborate effectively within remote and distributed teams. • Bonus Points: • Experience building or operating ML platforms on Databricks. • Scala development experience • Familiarity with ML workflow orchestration tools (e.g., MLflow, Kubeflow, Airflow) and interest in automating model development, testing, and deployment. • Exposure to generative AI or large language model workflows within an agentic or conversational UX context. • Experience designing developer-facing APIs or tools to empower other ML engineers or data scientists. • Success working in remote-first or globally distributed engineering organizations. <h3>🏖️ Benefits</h3> • Competitive salaries, meaningful equity, 401(k) plan • Medical, dental, vision, life insurance • Balance Days (additional paid holidays) • Fertility & Adoption Assistance • Paid Sabbatical • Flexible PTO • Monthly Employee Wellness allowance • Monthly Professional Development allowance • Pre-tax commuter benefits • Complete laptop workstation