RegulAItion’s mission, through analytics and automation, is to reduce the burden and risk of regulation, to empower people to work smarter and to free-up organisations to create, innovate and thrive.
We’re building great things including an incredible team. We challenge ourselves constantly and are always looking for new perspectives on old problems. New ways of thinking. New ways of working. We work with regulators and industry in large scale collaboration projects, harmonising our academic activities within University College London.
We work with major financial regulators and have access to large data sets. There is a strong greenfield element to the role for you to work creatively and with freedom. If challenge is appealing, we’d love to hear from you.
As an Engineer in Machine Learning at RegulAItion, you'll apply your expertise to implement infrastructure and product features necessary for our Machine Learning efforts. This includes infrastructure and tools for performing ML research, backend infrastructure to run ML models at scale, and product changes that use these models.
Skills and Experience
Advanced Computer Science knowledge, e.g. development and code review best practices, algorithms, data structures, object-oriented design, and design patterns.
- Ability to drive the ML ecosystem/architecture and deploy production-grade Python code.
- Experience in the development of REST applications in Python and Java applications.
- Capable of writing effective APIs.
- Experience with Data Visualisation tools.
- Familiarity with one or more Deep Learning software frameworks such as Tensorflow, PyTorch or Keras.
- Experience with some of the following Python libraries: Scikit-learn, Pandas, NumPy, Keras, Gensim, NLTK, Spacy, Flask.
- Experience with creating ETL/ELT pipelines.
- Demonstrated experience in Big Data architectures such as Hadoop/Spark.
- Experience with NLP (Word embeddings, Spacy, Recurrent Neural Networks) and NLP-specific techniques such as dependency parsing, part-of-speech tagging.
- Experience with NoSQL databases (MongoDB or Cassandra).
- Good communication skills in order to collaborate on productionising ML/NLP projects with the other data scientists and/or interact with RegulAItion’s clients in order to pitch/present on your ML implementation.
- Demonstrable experience with containerisation and orchestration
- Master’s Level qualification in a CS/Engineering or a numerically intensive field.
- Good theoretical grounding and practical experience in core machine learning concepts, techniques and frameworks, e.g. data cleanup and feature engineering, language models and word embeddings, SVMs, CNNs, RNNs
- Strong software engineering skills
We are building deep tech solutions that combine Distributed Ledger Technologies, Privacy Preservation cryptography and Machine Learning. We build resilient systems with great UX, employing SPA frameworks (such as Angular) and Pythonic & JVM languages (Java, Kotlin, Groovy) with a keen focus on Microservices architectures, to implement highly scalable business critical solutions. We recognise the need to build cloud agnostic solutions using Kubernetes to manage execution environments across a variety of cloud hosting providers such as GCP, AWS etc. Our stack is not limited to this however, we strongly encourage the use of different tools and environments provided that they have a demonstrated use case and benefit. You will be working with Data Scientists, Backend Engineers, Front End Engineers and Product staff in a highly Agile environment with a strong focus on shipping out business critical features with a high degree of regularity.
RegulAItion has a solid investment structure that allows us to offer competitive packages to the right candidates with the option of share schemes as the company grows.