ML Engineer - Modeling

Remote Full-time
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 DMARC Analyzer Suite Trusted Email. Delivered. It was founded in 2012, and is headquartered in Hilversum, Noord-Holland, NLD, with a workforce of 11-50 employees. Its website is
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