Machine Learning Engineer
About us
Our mission is to teach the next billion people English and become the de facto way people learn languages.
English is the global language of business, culture, and communication, and over 1.5 billion people around the world are actively trying to learn right now. The problem is that it's nearly impossible to learn to speak a language without constant access to a speaking partner. Grammar and vocab apps don't really help – you need to actually converse with someone.
Speak is on a journey to fix this. We're creating an AI-powered experience that replicates the flow of a conversation, without needing a human on the other end. The goal is to make it radically more accessible to be able to have conversations in English and eventually help hundreds of millions of people gain fluency who otherwise wouldn't be able to.
We started on this journey over four years ago and we've still got a long ways to go. We're thoughtfully adding new team members only when we think they can truly play a big role in our mission.
Speak is currently live in South Korea where we have quickly grown to become the top grossing education app in the country. We recently launched in Japan as well and are expanding to more markets in the coming months. The company is well funded, raising a recent Series B backed by investors like OpenAI, Founders Fund, Y Combinator, Khosla Ventures, Lachy Groom, Josh Buckley, and others. We’re a team of just under 40 based primarily in SF, Seoul, and Ljubljana.
About this role
We are looking for a passionate and experienced software engineer versed in building and deploying ML systems efficiently at scale. This is a very special opportunity for the right engineer to work on enormously impactful problems with clear solutions powered by real-world deep learning. As one of the first hires into the ML team, you will have a great latitude in shaping the direction of the ML roadmap and the infrastructural decisions.
What you’ll be doing
- Take ownership of productionalizing, optimizing, and scaling of machine learning systems to power speech and NLP-based product features
- Work on building a robust ML infrastructure that accelerates ML team output and enables continuous improvement - orchestration of pipelines, model versioning, data versioning, model monitoring, model serving, experimentation etc
- Bring in the best software engineering practices to a growing ML organization
What we’re looking for
- 5+ years of software engineering with versatile experience in ML systems
- Have a solid grasp on the MLOps ecosystem
- You have acquired best practices to lead the team towards building a robust ML infrastructure
- You obsess about SLAs
- Proficiency in programming languages and libraries (PyTorch) that enable efficient server-side deployments
- You have built high performance online serving infrastructure
- Experience in building ML products using cloud-based platforms
- Solid machine learning background and familiarity with standard speech, NLP, and machine learning techniques with experience with at least one major deep learning framework
- Experience with MLOps tools such as MLflow, Kubeflow, Metaflow, Airflow, Seldon Core, TFServing etc
- Autoscaling, containers, performance tuning and optimization
Why work at Speak
- Join a fantastic, tight-knit team at the right time: we're growing super quickly, we just raised our Series B from some of the top investors in the valley, and we've achieved product-market fit. You'd join at a magical time when a single person could significantly change the course of the company.
- Do your life's work with people you’ll love working with: we care strongly about our craft and want every person at Speak to feel like they're growing every day. We believe in the idea that working with people you both enjoy and have respect for makes everything better. We hire thoughtfully and only work with people we admire deeply.
- Global in nature: We're live in South Korea and Japan, and launching in a number of new markets soon. We have dedicated offices in San Francisco, Ljubljana, and Seoul, and you’ll have the opportunity to talk to users in each of these regions on a regular basis as well as travel.
- Impact people's lives in a major way: Learning a language is one of the single most life-changing skills one can learn and right now 99% of people never achieve their goal because the process is broken. We’re helping millions of people achieve their goals and improve their lives.