Richard Godden

Experience:

Throught Machine: Tech Lead Manager, Developer Experience

Responsible for the systems which get code from a developers machine to delivered ready for installation. We have an engineering department of over 300 developers contributing to a monorepo practicing continuous integration. We mainly develop in golang and deploy our microservice systems in kubernetes. Some of the main systems my team manage are:

• Woodhouse: an in house distributed scalable CI/CD system written in golang deployed with kubernetes which paralelises the tasks of building and testing our repo and vault our microservice product.
• Mettle: an in house distributed build system which implements the remote execution api remotely running builds and tests on a fleet of hundreds of workers. We run over 3 million tests a day on mettle as part of our CI process.
• Phabricator: The application we use for code reviews. We recently migrated our clustered self hosted instance to kubernetes automating the management of the component nodes with a tool we call Phacsimile.
• Cromwell: An in house system for automating the process of promoting versions of our product Vault through our environments to production.
• Aftermath: An in house test reporting system which processes and analyses the 3 million tests we run daily providing reports and automating tasks like highlighting flaky tests.

Glemore Gas: Technical Manager

• Petra: Identified opportunities for oil field development using production and geological data, Developed modules within geological analysis systems to streamline work flows.
• Sharepoint online: Implemented sharepoint platform for business

Ebico Oxford: Commercial Projects Manager

• Energy-supply business: Project manager for the development plan to set up a new, branded business model.
• Commercial: Developed key business-to-business relationships with external partnerships and suppliers and negotiated contracts and services.
• Cloud services transition: Project managed the companies transition to a cloud computing system

E2V Technologies Plc: Continuous Improvement Champion and Analyst

• Manufacturing Capacity: developed SAP software to analyse and reduce capacity constraint on S&OP process.
• Magnetron business: Developed forecasting tools to predict requirements of a key customer and assisted in the development of a more protable contract.
• Global sales: Ran the weekly global sales forecasting system and presented it to the Executive Committee, analysing changes to the forecasts and highlighting key opportunities.

Havelock Europa Plc: Associate, Operations

• Time log: Automated the time log booking on contracts within CIMPAC system eliminating manual task
• On-time Delivery & QA: Managed a team of 14 to analyse failures, implementing preventative process.

Education:

Columbia University: Masters of Science in Computer Science

I graduated from my masters in computers science at Columbia. I was particularly interested in machine learning including deep learning but also gained a passion for systems development which guided my choice to become a software engineer rather than data scientist. I studied computational neuroscience to get a better understanding of the algorithms in the brain.

University of Cambridge: MA, Mathematics

I graduated from Cambridge University in 2009 having studied Mathematics with a particular focus on statistics. Between then and my masters I worked for seven years in a wide variety of technical and business roles in industries from manufacturing, electronics to energy supply.

Classes:

• Operating Systems - Jason Nieh
• Big data analytics - Dr. Ching-Yung Lin
• Bayesian machine learning - John Paisley
• Advanced Machine learning - Lior Horesh & Julie E. Novak
• Advanced Programming - Jae Woo Lee
• Deep Learning for Computer Vision, Speech, and Language Liangliang Cao & Xiaodong Cui
• Introduction to databases - Alex Biliris
• Machine learning - Daniel Hsu
• Analysis of algorithms I - Alexandr Andoni
• Neural networks and deep learning - Zoran Kostic
• Computational neuro-science: circuits in the brain - Aurel Lazar

Projects:

• Linux development: Implemented a weighted round robin scheduler with load balancing, a filesystem to track gps and created system calls to inspect the process graph, wake processes on motions and expose virtual-physical memory maps.
• Artistic style transfer Implemented a neural network to transfer artistic style in theano.
• Passenger screening: Detected items of contraband/weapons from 3d scans of passengers with 99% accuracy using deep residual neural networks.
• Web server: Built a web server from scratch in C hosting a database including creating linked list data-structures, database reading and writing, network communications and front end html.
• Fake news challenge: Used various machine learning algorithms including random forest, SVM, KNN and LSTMs to predict whether a headline and news article body: agree, disagree, are neutral or unrelated.
• Music styles: Inspired by word2vec, learned embeddings for chords to classify style based on chord progressions.
• Larvae neural-muscular simulation: Simulated the motion of a larvae by modeling the interaction between neurons and muscular mechanics.

Technical Skills

• Languages: Golang, Python, C, C++, SQL
• Technologies: Kubernetes, Containers, GCP, AWS, Linux, Tensorflow, Theano, Hadoop, Spark

Other things

I dance salsa, bachata, kizomba and brazilian zouk. I have recently started climbing or more acurately falling from about 4m. I am an artist particularly figure drawing and painting and very occasionally dust off my saxophone and clarinet.