ML Engineer - Modeling

Mimecast is a company focused on cybersecurity innovation and impact, seeking a Machine Learning Engineer to join their expanding ML team. In this role, you will develop and deploy cutting-edge NLP, computer vision, and speech recognition models, contributing to the company's proprietary ML products and collaborating with various teams to enhance customer-facing predictive models.

Responsibilities

• Research, design, develop and maintain state-of-the-art NLP, computer vision and speech recognition models that are optimised for accuracy, latency and throughput
• Train and evaluate NLP, computer vision and speech recognition models
• Collaborate with diverse teams from Product, Engineering, Marketing, Customer Success, and Sales to develop customer-facing predictive models to be deployed on the AI platform; working independently with Product to conceptualise, research, and develop new features
• Work alongside other ML enthusiasts and lead projects that result in production deployments for thousands of customers
• Design and implement end-to-end data and ML pipelines capable of feeding real-time data products. This will include interacting with a variety of data tools to source, clean, and feature engineer raw data; productionise and deploy ML models; and monitor those models for efficacy, throughput and latency
• Communicate your work, for example by giving regular knowledge sharing sessions in front of ML experts and engineers of different teams
• Own, shape, and prioritize your work with little to no oversight from Scrum Master or Engineering Manager
• Collaboration is a key factor of success. You will work in a team where everyone shares ownership and responsibility, everyone pushes one another to give the absolute best, and everyone tries to be a support for each other every day. You’ll also work with a variety of other teams, quickly and proactively establishing strong relationships with key stakeholders
• Providing recommendations and strategies to manage scalability, tuning and other configurations within the data infrastructure
• Mentor and guide junior members of the team, establish and champion best practices and introduce fresh ideas and concepts from the ever-evolving research world of NLP
• Understand and influence software architecture decisions to enable the delivery and analysis of high-volume datasets

Skills

• Experience working in ML, with 1+ years developing large-scale NLP, computer vision and/or speech recognition systems that are deployed to production environments
• Must have solid programming skills in Python, along with experience in using relevant tools and frameworks such as PyTorch, NLTK, Spacy, OpenCV, Tesseract and Huggingface
• Must have solid foundational knowledge about linear algebra, stochastic optimisation and probability theory
• Ph.D. or Master's degree in a quantitative field (computer science, statistics, mathematics) and typically at least 1 year of experience applying advanced ML modelling techniques to problems in industry, or Bachelor's degree with typically at least 3 years of experience applying advanced ML modelling techniques to problems in industry
• Deep theoretical knowledge of topics such as statistical inference and machine learning, including experience with forecasting and time series analysis, hypothesis testing, anomaly detection, classification, and regression
• Extensive experience developing natural language processing (NLP); computer vision; or predictive statistical models on large datasets
• Strong analytical and problem-solving abilities, with a keen eye for detail and accuracy
• Curiosity and a strong growth mindset with a demonstrable history of learning quickly in a loosely structured, rapidly changing environment
• Excellent collaboration and communication skills
• Experience working with large (more than 2 million training examples) and highly unbalanced datasets is a plus
• Proficiency with AWS data pipeline technologies such as Kinesis, Lambda, S3, Elasticsearch and EMR (Hadoop or Spark) as well as ETL tools like Apache Airflow
• Proficiency using code orchestration tools like Apache Airflow, DVC, or SageMaker Pipelines

Benefits

• Comprehensive benefits package that helps our employees and their family members sustain a healthy lifestyle
• Incentive plans
• Formal and on-the-job learning opportunities

Company Overview