Senior Machine Learning Engineer, Iterable

• This is an exceptional opportunity for someone with a strong platform mindset who is passionate about building end-to-end ML workflows, enjoys tackling real-world data problems, and thrives on ownership from ideation through to deployment
• Have 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
• Show proficiency with Python (with a preference for experience in distributed data processing environments like Databricks, Spark, or similar platforms)
• Bring 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
• If this is a role that excites you, please do apply as we value applicants for the skills they bring beyond a job description

Desirable

• We’re looking for a talented Senior Machine Learning Engineer to join a cross-functional machine learning team shaping the future of our platform’s AI capabilities
• In this role, you’ll architect and develop robust systems for feature engineering and large-scale model training — collaborating across teams, navigating complex data challenges, and guiding technical direction
• You’ll play a pivotal part in designing reusable, scalable ML infrastructure, enabling teams to accelerate experimentation and bring intelligent features to life
• While specific domain expertise in certain ML methods is a plus, what matters most is your ability to identify impactful opportunities, prototype new solutions, and continuously advance our platform’s machine learning capabilities
• One of our core values is a growth mindset and Iterable is a company where everyone can grow
• 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 our partners to reach the right user with the right message at the right time
• Own the complete lifecycle of ML platform features: from requirements gathering and architecture, through implementation, deployment, and post-launch support
• Shape architectural decisions aimed at building robust, reusable, and highly available ML infrastructure that raises the bar for engineering and data science excellence
• Mentor colleagues through code reviews, technical design sessions, and knowledge sharing, helping grow a strong culture of engineering rigor and learning