Startup engineering is a podcast that goes behind the scenes at startups. Rob De Feo, startup advocate at AWS your host will talk to engineers, CTO’s, and founders that built the technology and products at some of the world's leading startups. Each episode we will learn the inside story of how they overcame their biggest technology challenges. From launch through to achieving mass scale, and all the bumps in between. Experts share their experiences, lessons learnt and best practices. If you are excited about working at or building the next big thing or you want to learn from the engineers that have been there and done that, subscribe to the startup engineer wherever you get your podcasts.
Find out more about Ably and Paddy and be sure the checkout their GitHub profile.
Resources:https://www.finbourne.com/https://en.wikipedia.org/wiki/Bitemporal_Modelinghttp://github.com/finbournehttps://www.lusid.com/
Luca is an entrepreneurial Technology Leader, working with startups and scaleups in creating the next wave of innovation. Currently he’s the VP Engineering of Signal AI where he leads the Product & Technology provision. Prior to that, he was Strategy Product Lead at uSwitch.com, the leading UK comparison website. His experience also involves high level technology consultancy assisting clients in digital transformation and creation of new digital products. He worked as a Lead Consultant for ThoughtWorks, focussing on the European markets.Resources:Luca's blog - https://www.lucagrulla.com/SignalAI research blog: https://research.signal-ai.com/SignalAI GitHub - https://github.com/signal-ai/
As one of five co-founders, Anatol started work on the backend and infrastructure of SimScale while studying Computer Science at TU Munich and Georgia Tech. Today, with SimScale being both on a sound technological footing and a successful business, he and his team work on anything infrastructure – from typical topics like CI/CD, data storage, or provisioning cloud resources cost-efficiently and conveniently as needed by users and developers, to cross-cutting concerns like security or privacy. He also enjoys finding great new talent – if you want to find out more about the unique and fun challenges at SimScale. Get in touch on LinkedIn, Twitter, Facebook, YouTube or Instagram.ResourcesCloud based collaboration - https://www.simscale.com/blog/2020/03/cae-collaboration-features/Running desktop applications in the cloud https://www.simscale.com/blog/2019/09/non-cloud-native-services/SimScale are hiring https://www.simscale.com/jobs/
Marc Fletcher graduated with a PhD in Physics (Quantum Computing) from the University of Cambridge and has been the CTO at Echobox since 2014. Whilst not jumping out of planes or competing for GB as a professional skydiver, he’s particularly passionate about maximising productivity in high performance cross-functional technology teams.Resources:Data first remote working perspective - https://medium.com/echobox/in-search-of-higher-engineering-productivity-a-data-first-remote-working-perspective-ab4a47f4417aNicole Forsgren - Author of Accelerate: The Science of Lean Software and DevOps, and is best known for her work measuring the technology process and as the lead investigator on the largest DevOps studies to date.Echobox are hiring - https://careers.echobox.comGithub Organization - https://github.com/ebxAWS resources for remote working - https://aws.amazon.com/blogs/aws/working-from-home-heres-how-aws-can-help/
Our guest Malte Pietsch is a Co-Founder of deepset, where he builds NLP solutions for enterprise clients, such as Siemens, Airbus and Springer Nature. He holds a M.Sc. with honors from TU Munich and conducted research at Carnegie Mellon University.He is an active open-source contributor, creator of the NLP frameworks FARM & haystack and published the German BERT model. He is particularly interested in transfer learning and its application to question answering / semantic search.Resources:Deepset - Make sense out of your text data - https://deepset.ai/FARM - Fast & easy transfer learning for NLP - https://github.com/deepset-ai/FARMHayStack - Transformers at scale for question answering & search - https://github.com/deepset-ai/haystackSageMaker - Machine learning for every developer and data scientist - https://aws.amazon.com/sagemaker/Spot Instances - Managed Spot Training in Amazon SageMaker - https://docs.aws.amazon.com/sagemaker/latest/dg/model-managed-spot-training.htmlElasticSearch - Fully managed, scalable, and secure Elasticsearch service - https://aws.amazon.com/elasticsearch-service/Automatic mixed precision - Automatic Mixed Precision for Deep Learning - https://developer.nvidia.com/automatic-mixed-precisionPyTorch - Open source machine learning framework that accelerates the path from research prototyping to production deployment - https://pytorch.org/NumPy - Fundamental package for scientific computing with Python - https://numpy.org/MLFlow - An open source platform for the machine learning lifecycle - https://mlflow.org/BERT - Bidirectional Encoder Representations from Transformers - https://en.wikipedia.org/wiki/BERT_(language_model)SQuAD - The Stanford Question Answering Dataset - https://rajpurkar.github.io/SQuAD-explorer/Sebastian Ruder - Research scientist at DeepMind - https://ruder.io/Andrew Ng - His machine learning course is the MOOC that had led to the founding of Coursera - https://www.coursera.org/instructor/andrewng
Stuart has been a coder since he was 13 and professionally for the last 15 years. He has worked in various London startups since 2011. In 2016 Stuart eventually bit the bullet and co-founded Zego, a micro-insurance startup for the gig economy. Zego is a global insurtech business providing flexible commercial insurance for businesses and professionals.Resources:Zego BlogAWS Activate founder tier providers $1,000 in AWS Credits,access to experts and the resources needed to build, test & deploy. Activate your startup today.How to break a monolith application into microservices using ECS and Docker.
Startup Engineering host Rob De Feo goes behind the scenes at startups. We hear from the engineers, CTO’s, and founders that built the technology and products at some of the world's leading startups. Each episode we will learn the inside story of how they overcame their biggest technology challenges. From launch through to achieving mass scale, and all the bumps in between. Engineers share their experiences, lessons learnt and best practices.