Senior Machine Learning Engineer

How you will make an impact:

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.

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. 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. If this is a role that excites you, please do apply as we value applicants for the skills they bring beyond a job description.

How You Will Make a Difference:

• 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.

We Are Looking for People Who:

• 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.

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.

Perks & 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

The US base salary range for this position at the start of employment is $133,500 - $212,000. Within this range, individual pay is determined by specific US work location, as well as additional factors, including job-related skills, experience, relevant education or training, and internal equity considerations.

Please note that the range listed above reflects only base salary. The total compensation package includes variable pay (where applicable), equity, plus a range of benefits, including medical, dental, vision, and financial. In addition, we offer perks such as generous stipends for health & fitness and learning & development, among others.