Machine Learning Engineer II

Machine Learning II Engineer – Incydr Product Development

Mimecast is at the forefront of the cybersecurity industry, delivering innovative solutions to protect businesses and individuals from evolving threats. Our mission is to empower organizations with secure and scalable technology that stands resilient in the face of cyber challenges.

We are seeking a Machine Learning Engineer II to join our product development team working on Incydr, our Insider Risk Management product. In this role, you will embrace the role of "full-stack" data scientist, which will often require you to acquire and clean raw data, engage internal and external partners to obtain labels for that data, develop machine learning and statistical models, deploy models to production, and monitor the models for performance.

Beyond your technical skills, you will be asked to lead ML-based initiatives that are leveraged across the breadth of our solutions. It is expected that you will understand the business context and challenges as well as articulate practical solutions. You will also collaborate with other development teams and cross functional teams to provide features that bring value to our customers and help them secure their collaboration culture.

Mimecast is an AI-first engineering organization. Machine Learning engineers at Mimecast are empowered to use AI development tools every day—to explore ideas, prototype quickly, interpret data and experiment results in order to advance modeling work with clarity and pace. That is how we work; it is not an add-on. You will build systems that embed AI directly into the product, including LLM and agent-based patterns.

Fluency in designing modern AI architectures - including LLM and agent-based systems - is a core expectation of the job from day one.

• Research, design, develop, and maintain state-of-the-art machine learning models optimized for accuracy, latency, and throughput.
• Train, evaluate, and fine-tune models using best practices in model selection, validation, and performance optimization.
• Provide recommendations and strategies to manage scalability, tuning, and other configurations within the data infrastructure.
• Stay up-to-date with the latest advancements in ML/AI and proactively introduce innovative ideas and concepts from current research.
• Design and implement robust, end-to-end data and ML pipelines capable of feeding real-time data products.
• Source, clean, and perform feature engineering on raw data using a variety of data tools and frameworks.
• Productionize and deploy ML models, ensuring seamless integration with existing systems.
• Monitor deployed models for efficacy, throughput, and latency, and iterate as needed to maintain optimal performance.
• Understand and influence software architecture decisions to enable the delivery and analysis of high-volume datasets.
• Lead and deliver ML projects from conception to production deployment, impacting thousands of customers.
• Mentor and guide junior team members, establish and champion best practices, and foster a culture of continuous learning and improvement.
• Collaborate with diverse teams including Product, Engineering, Marketing, Customer Success, and Sales to develop customer-facing predictive models.
• Work independently with Product to conceptualize, research, and develop new features that drive business value.
• Communicate complex technical concepts clearly and effectively, including giving regular knowledge-sharing sessions to ML experts and engineers across teams.
• Collaborate with teammates throughout the product development organization, including product owners, User Interface/User Experience Designers, Quality Assurance Analysts, Technical Writers, and Customer Champions.
• Own, shape, and prioritize your work with minimal oversight, demonstrating strong self-management and accountability.
• Proactively establish strong relationships with key stakeholders, quickly building trust and rapport across the organization.
• Take initiative to learn about new technologies and methodologies, sharing insights and fostering a culture of curiosity and growth.
• Foster a collaborative team environment where…