Senior Machine Learning Engineer (Nova)

Iterable is the leading AI‑powered customer engagement platform that helps leading brands like Redfin, SeatGeek, Priceline, Calm, and Box create dynamic, individualized experiences at scale. Our platform empowers organizations to activate customer data, design seamless cross‑channel interactions, and optimize engagement—all with enterprise‑grade security and compliance. Today, nearly 1,200 brands across 50+ countries rely on Iterable to drive growth, deepen customer relationships, and deliver joyful customer experiences. Our success is powered by extraordinary people who bring our core values—Trust, Growth Mindset, Balance, and Humility—to life. We foster a culture of innovation, collaboration, and inclusion, where ideas are valued and individuals are empowered to do their best work. That’s why we’ve been recognized as one of Inc’s Best Workplaces and Fastest Growing Companies, and were recognized on Forbes’ list of America’s Best Startup Employers in 2022. Notably, Iterable has also been listed on Wealthfront’s Career Launching Companies List and has held a top 10 ranking on the Top 25 Companies Where Women Want to Work. With a global presence—including offices in San Francisco, New York, Denver, London, and Lisbon, plus remote employees worldwide—we are committed to building a diverse and inclusive workplace. We welcome candidates from all backgrounds and encourage you to apply. Learn more about our story and mission on our Culture and About Us pages. Let’s shape the future of customer engagement together! Position Overview We are looking for a Senior Machine Learning Engineer to build the core Machine Learning foundations that power Nova’s agentic experiences. This role focuses on applied Machine Learning in production environments: retrieval systems, evaluation frameworks, and model integration layers that make AI features reliable, scalable, and repeatable. You will design and implement the underlying components that support rich, intelligent interactions in the Iterable platform. You will work closely with backend, frontend, and product teams to shape how Machine Learning is introduced and maintained across the company. The work blends hands‑on engineering with system design, and is ideal for someone who can drive complex efforts independently, make practical architectural decisions, and collaborate in a fast‑moving, cross‑functional product environment. Responsibilities Design and build Machine Learning platform components that support agentic systems, including retrieval pipelines, indexing strategies, and model integration layers. Introduce and operationalize RAG use cases, from data sourcing and embedding generation to runtime retrieval patterns. Develop generalized evaluation frameworks for LLM- and agent-based features, including offline metrics, golden datasets, and continuous monitoring. Implement abstractions, tooling, and reusable patterns that enable other teams to build ML- and LLM-powered experiences efficiently. Partner with backend engineers to productionize ML features with strong reliability, observability, and performance characteristics. Prototype applied ML solutions to validate feasibility before investing in full builds. Ensure secure, robust handling of data used in ML workflows and retrieval operations. Collaborate with product, design, and engineering to align ML system design with user experience and product goals. Contribute to iterative improvements of the Nova agent framework, including workflows built with Mastra and TypeScript. Qualifications 5+ years experience as a Machine Learning Engineer or similar role focused on production systems. Strong engineering skills with Python or TypeScript, including experience building ML workflows in frameworks like Mastra or comparable agent/LLM toolkits. Experience with retrieval systems, vector databases, search technologies, or RAG architectures. Prior work integrating ML or LLM-powered features into production applications. Understanding of ML evaluation techniques, experimentation design, and failure analysis. Ability to lead complex projects, make practical trade‑offs, and work independently in areas of ambiguity. Strong communication and collaboration skills in a distributed environment. Bonus Points Experience building ML or LLM platforms, tooling, or developer-facing frameworks. Prior work with embeddings, search–ranking systems, or advanced RAG architectures. Familiarity with event-driven systems or streaming architectures. Experience with model observability, performance monitoring, or proactive regression detection. Background in personalization, recommendations, or applied NLP. Experience working in remote‑first engineering teams. 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. Recruitment Disclaimer Send job offers from free email services like Gmail, Yahoo mail, Hotmail, etc. (❌ We do not send job offers this way.) Request money, fees, or payment of any kind from prospective candidates to apply to Iterable, for employment, or for the recruitment process (e.g. for home office supplies, or training, etc.). (❌ We do not request money.) Request or require personal documents like bank account details, tax forms, or credit card information as part of the recruitment process prior to the candidate signing an engagement letter or an employment contract with Iterable. (❌ We do not request these.) 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