Senior Machine Learning Engineer

Summary

Join Iterable, a leading AI-powered customer engagement platform, as a Senior Machine Learning Engineer. You will architect and develop robust systems for feature engineering and large-scale model training, collaborating across teams and tackling complex data challenges. This role offers the opportunity to build end-to-end ML workflows, design scalable ML infrastructure, and mentor colleagues. You will play a pivotal role in shaping the future of the platform's AI capabilities, bringing intelligent features to life. Iterable values a growth mindset and encourages applications from individuals with diverse skills. The company offers a competitive salary and benefits package.

Requirements

• 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

Responsibilities

• 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

Preferred Qualifications

• 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

Benefits

• 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