ML Engineer - Modeling

Mimecast•Lexington, MA

1d•$120,000 - $180,000•Hybrid

About The Position

Machine Learning Engineer Embrace the incredible opportunities that lie within Mimecast, where innovation and impact converge. The cybersecurity industry is experiencing exponential growth, and by joining us, you'll be at the forefront of this ever-evolving landscape. The field is rapidly changing, as threat actors employ AI to scale up phishing and social engineering operations. You'll have the chance to develop and utilise cutting-edge NLP models, empowering you to thwart these cyber villains and safeguard businesses and individuals alike. As a company that is well-established and committed to growth, we are actively expanding our ML team with a ML Engineer II role which is amongst the most roles in the team. Join us on this exhilarating journey, where you'll shape the future of cybersecurity by developing large-scale Natural Language Processing (NLP), computer vision, and speech recognition models that push the boundaries of innovation and make an indelible impact in protecting our digital world. As a ML Engineer II at Mimecast you will embrace the role of a full-stack ML Engineer, which will often require you to acquire and clean raw data, engage internal and external partners to obtain labels for these data, develop ML and statistical models, deploy models to production, and monitor the models for performance. You will be contributing to the development of our proprietary ML products, repositories of solutions, and helping engineering teams leverage our existing models and expertise to aid with better insights to their data. Beyond your technical skills, you will be asked to lead ML-based initiatives that are leveraged across the breadth of our solutions.

Requirements

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

Nice To Haves

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
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

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

Benefits

Mimecast offers formal and on-the-job learning opportunities, maintains a comprehensive benefits package that helps our employees and their family members sustain a healthy lifestyle, and importantly – working in cross functional teams to build your knowledge!
We provide you with the flexibility to live balanced, healthy lives through our hybrid working model that champions both collaborative teamwork and individual flexibility.

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