Our speech process system translates videos into the World’s languages without losing the characteristics that make each individual’s voice unique.

It’s a unique technology that has never existed before. This is only possible with a great engineering team composed of talent from Cambridge, Oxford, NYU, and UCL, and we have the world’s leading academics in speech processing - Simon King and Mark Gales as our advisors.

We’re looking for machine learning engineers who are comfortable with frameworks such as TensorFlow and PyTorch, or are willing to push themselves to know these frameworks like the back of their hand.

We’re also looking for full-stack (Python/JS) developers who are customer oriented and have the ability to keep iterating the client-facing self-service platform as we navigate unexplored territories. Our developers also work closely with ML Engineers to streamline the pipeline, and enforce the discipline needed for a tidy, clean, production-ready code-base.

In order to best serve our global, creative community, we’re constantly evolving and iterating on our technology.

In addition to working on day-to-day tasks and projects, our team has the space to explore emerging technologies they’re interested in via self-learning, engineering conferences, and/or alternate forums. For example, our team recently attended TensorFlow Dev Summit, Google I/O, and Android Dev Summit.

We’re working in completely new spaces, particularly for mobile. Our Machine Learning team is focused on creating meaningful user experiences in social and creative spaces, rather than using ML to drive ads. One recent feature that demonstrates this is For This Photo, which automatically recommends presets based on the type of image you upload.

Even though we’re foraying into new spaces from a technology stance, we don’t expect candidates to be familiar with every technology we use. For example, our Android team shifted to Kotlin, but we’re open to adding on folks without direct experience in Kotlin. At the end of the day, we’re looking for candidates who are inherently curious and hold a growth mindset when it comes to finding and learning new technologies aligned with our mission.

We’re using technology to build for the bigger purpose of human creativity and celebrating differences. The challenges we’re solving related to ML, photography tools and creative expression on mobile platforms are novel. We take an avid interest in emerging technology and how we can use it to enhance these experiences in unexpected ways.

A lot of what we do hasn’t been done before.

In fact, when Grammarly was founded in 2008, the concept of using AI to facilitate communication was a completely new concept. We managed to build something that was profitable right from the get-go because we were interested in solving problems at the next frontier, and we still continue to be today. We’re always ready to try out and adopt new technologies (check out our tech stack below for the variety of languages, tools, and frameworks we use both internally and in production). And we’ll often customize open-source tools for our own use, like building a custom layer on top of Docker. It’s also very common for our engineers to spontaneously give talks and tutorials on the things that interest them. We have a group of functional-programming evangelists, and one of the most recent talks was called “Fighting God Object with Monads.”

Check out our tech blog for the challenges we’re working on.

We are platform agnostic.

Software for new hardware is what we do best, and our engineering team is constantly experimenting with new technologies. Currently, our team is excited to work on VUI (voice) projects and expand our AI/ML practice. We are working very closely with industry AR/VR leaders and undertaking interesting and unique applications of these technologies.

We are constantly adding new technologies to our stack to make our software development process faster and more efficient.

We are fans of open source projects and believe in not reinventing the wheel. We use a new PHP7 framework called Laravel to power our API layer. It gives PHP super-powers like command line tools, dependency injection, ORM, queues and schedules, event listeners, and so forth. We also use Vue.js to power our front-end application in addition to other technologies like Redis, MongoDB, MySQL, Jenkins, Express and node.js.

Ohhhhh shiny!

Our stack includes Ruby on Rails, NodeJS/Serverless, and DynamoDB, just to name a few. We aim to increase developer velocity by using new technologies with large community resources. We realize that building applications with dated technology discourages other people from wanting to work with us and lowers our educational resources online. Open source technology has allowed us to get answers to our questions faster, which in turn has helped us build faster. We ship code everyday and are constantly rolling out new features to our customers. We decide what needs to be built and then we look at which technology will get us there the fastest. You may not have experience with the Serverless Framework, but as long as you are open to learning it, we are open to teaching it to you!

We use Reactive programming, event sourcing, and MVVM.

As a team, we’re very open to adopting new technologies. In fact, we’re constantly looking for the best tools for the job and if we can’t find it, we’ll develop our own (we developed our own ink engine and also built the foundation for collaboration). While we are very deliberate about the technologies we use, we don’t require engineers to have experience with any of them beforehand. We believe that anyone can learn a new language on the job. If anything, one of the most important attributes we look for in candidates is having a growth mindset.

We’re building on the Lightning Network, a new Layer 2 network built on top of Bitcoin.

When we started, Lightning wasn’t even in Beta, so we’re right on the bleeding edge. This choice in technology has come with its fair share of challenges (i.e. we’ve had to implement key features ~6 months before they get upstreamed), but it has also allowed us to build significant new features that were never before possible, and these key features are our differentiators. Our ability to trade cross-chain, giving access to real Bitcoin, and our high performance without sacrificing custody is our core product and value and both are the result on building on this brand new platform.

We predict that in 5 years, there will be far more engineers working on Bitcoin, cryptocurrency, and Lightning than there are today, and we want Sparkswap to contribute to that growing trend. A core competency of the company is to bring in people who are interested and enthusiastic about our technology and teach them how to work with it. In other words, you are not required to have experience with Lightning to apply or join. (If we had this criteria, we’d be limited to about 200 engineers worldwide :)

We focus on the right technologies for the job and pivot when needed.

We hold regular architecture review meetings where all team members can present how they are proposing to solve a problem, including what new technologies might be used. At Billtrust, a combination of architectural standards and team-based decisions drive the adoption of new technologies. For example, we had three scrum teams accustomed to building monolithic traditional three-tier manually tested software transition to containerized microservices with full CI/CD using a 70% different tech stack, on AWS, in one year.

Our microservices architectures are inherently platform vs. vertical application-oriented which allows for massive reuse and rapid time to market execution. We believe in full CI/CD pipeline implementation and we rabidly pursue automating everything. Our next-gen Quantum platform is distributed, event-driven and leverages a microservices architecture — it’s written from the ground up as cloud-native, which enables us to build scalable, reliable systems and quickly iterate.

Full-stack experience is very helpful as well as some experience with cloud-based platforms. That said, no engineer is going to know everything and we are open to hiring engineers who are willing to learn on the job. If you are language agnostic, know how to deliver incrementally without having to 'gold plate' software, see the value in CI/CD, and love to learn, we’d love to meet you. We provide a fair amount of opportunity for learning on the job, pairing with other engineers who have different skills, and regular lunch-and-learns.

Build with the latest and greatest.

Our stack includes GraphQL, React, React Native, TypeScript, and Ruby. We ship every day to our server as well as our web, mobile, and iPad apps. We’re committed to using new technologies to improve our development process and speed. A typical week looks like a quick sprint planning meeting to decide on which features we want to build, daily standups to measure our progress, and a high-degree of autonomy to build quickly.

We’re reinventing the advertising technology stack for conversational interfaces.

At EyeLevel.ai, we are re-imagining many components of the digital advertising technology stack for a fast-approaching future where the interfaces to our computers are conversational. Advertising through these new interfaces will resemble personalized, contextually relevant brand recommendations. In order to deliver an advertisement through conversation, we must accurately interpret and classify what users are saying through colloquial spoken or written language. Then we have to maintain a sufficiently rich context: not just what has been said last but also what has been said in the past, what the user is interested in, what their current emotional states is, etc. We must then match this context to brand recommendations with a high degree of accuracy. Failing to do so is not just ineffective for the brands, but also potentially upsetting for the users and our developer partners.

To solve these challenges, we use some of the most well-known machine learning and natural language processing tools, frameworks, and algorithms (RNN, Tensor Flow, etc.). But that’s not enough. We are also inventing solutions to bridge the gaps in these relatively new, evolving technologies. At EyeLevel.ai, there is an opportunity to make contributions to the machine learning community and to push the ecosystem forward in meaningful ways. The very nature of the market and challenges we are facing as a company demand it.