Senior Machine Learning Engineer, Iterable

• Masters or PhD in CS, Math, Physics, or similar engineering/science discipline or equivalent practical experience
• Experience with machine learning algorithms and tools, artificial intelligence, deep learning, natural language processing, or other ML disciplines
• Expertise with data exploration, visualization, and SQL queries
• Experience with large-scale data and commercial ML platforms
• Prior industry experience building end-to-end machine learning systems and shipping to production
• Proficiency in problem-solving and analytical skills, with proven experience in innovating solutions for complex challenges
• Strong communication skills and are adept at conveying technical concepts to non-technical stakeholders and collaborating across teams

Desirable

• As a Senior Machine Learning Engineer at Iterable, you will be leading data projects to launch new machine learning products and improve the predictive features in our core platform. We serve large and small companies spanning many different industries and have the opportunity to work with large and diverse data sets. You’ll also get to influence the decisions and policies we adopt as a company in this exciting era of AI
• One of our core values is a growth mindset, and Iterable is a company where everyone can grow. If this role excites you, please do apply, as we value applicants for the skills they bring beyond a job description
• Collaborate with engineers, product managers, and cross-functional development teams to integrate AI/ML technologies into product offerings that will allow customers to better target and personalize messages
• Evaluate and validate algorithm performance to ensure reliability, robustness, and generalization across datasets and scenarios, and present them to stakeholders
• Develop, and maintain machine learning pipelines for Iterable’s suite of data products using Spark, Scala, and Python
• Own end-to-end ML development from prototyping to deploying to production to enable AI features at scale
• Decide when to use out-of-the-box solutions vs. building custom solutions and utilizing both
• Work closely with other machine learning and data platform engineers to improve the tools and processes used for developing data products
• Mentor junior engineers, providing guidance, support, and technical leadership in AI algorithm development and best practices, especially in the deep learning and language modeling space
• Maintain expertise in the latest advancements in AI technology, exploring innovative approaches and techniques for practical application