Machine Learning Engineer II

Mimecast • Minneapolis, MN

13h • £124,000 - £186,000 • Hybrid

About The Position

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. AI-First Engineering at Mimecast 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.

Requirements

• Hold a Ph.D. or Master’s degree in a quantitative discipline (such as computer science, statistics, or mathematics) with a minimum of four years’ experience applying advanced machine learning techniques to real-world industry challenges, or possess a Bachelor’s degree with at least six years of directly relevant experience.
• Demonstrate advanced programming proficiency in Python, C++, Java, or Kotlin, and possess hands-on expertise with leading tools and frameworks including PyTorch, NLTK, Spacy, OpenCV, Tesseract, and Huggingface.
• Exhibit a robust understanding of linear algebra, stochastic optimization, and probability theory, with a proven ability to translate these concepts into practical real-world solutions.
• Possess deep theoretical and practical knowledge of statistical inference and machine learning, with experience in forecasting, time series analysis, hypothesis testing, anomaly detection, classification, and regression.
• Have a track record of working with large-scale datasets (exceeding two million training examples) and effectively managing highly imbalanced data.
• Be proficient in utilizing AWS data services such as ECS, Kinesis, Lambda, S3, Glue, Sagemaker, Bedrock, Athena, RDS, and Redshift for scalable data processing and deployment.
• Demonstrate experience in architecting and deploying scalable generative AI services leveraging frameworks such as Langchain, Llamaindex, n8n, and springAI
• Show capability in developing and maintaining infrastructure-as-code to automate and streamline the deployment of team-owned services.
• Be experienced in using version control systems to manage and collaborate on codebases efficiently.
• Have a strong understanding of handling sensitive data in accordance with Master Service Agreements and compliance requirements.
• Display exceptional analytical and problem-solving skills, with meticulous attention to detail and accuracy.
• Exhibit intellectual curiosity and a strong growth mindset, with a proven ability to learn rapidly in dynamic, loosely structured environments.
• Take ownership of deliverables and demonstrate accountability as an integral member of a collaborative team.
• Thrive in a cooperative work environment, readily offering and seeking assistance to achieve shared goals.
• Adapt seamlessly to shifting priorities and demands in a fast-paced setting.
• Communicate effectively and comfortably with non-technical colleagues and stakeholders.
• Show a genuine passion for designing and delivering robust, high-quality solutions.
• Excel in both collaborative and independent work, with outstanding communication and teamwork abilities.
• Articulate complex technical concepts clearly to peers in both written and verbal formats.
• Effectively convey the business implications of technical decisions to non-technical audiences.

Responsibilities

• 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 everyone shares ownership and responsibility, supports one another, and strives for excellence.
• Mentor and support junior staff, helping them grow their skills and confidence.
• Champion a supportive and inclusive team culture, encouraging open feedback and continuous improvement.

Benefits

• formal and ‘on the job’ learning opportunities
• comprehensive benefits package that helps our employees and their family members to sustain a healthy lifestyle
• working in cross functional teams to build your knowledge

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree