Staff ML Engineer

LILT is the leading AI solution for enterprise translations. Our stack made up of our Contextual AI Engine, Connector APIs, and Human Adaptive Feedback enables global organizations to adopt a true AI translation strategy, focusing on business outcomes instead of outputs. With LILT, innovative, category-defining organizations like Intel, ASICS, WalkMe, and Canva are using AI technology to deliver multilingual, digital customer experiences at scale.

While our core AI technology might share similarities with ChatGPT and Google Translate, it's what we do with it that makes LILT truly revolutionary. Our patented Contextual AI Engine goes beyond basic translations, understanding the nuance of our customer's content and target audience to deliver hyper-accurate, business-focused results. Our connector-first approach seamlessly integrates with our customer's existing workflows, and our human-adapted feedback loop ensures continuous improvement, making LILT a constantly evolving AI partner for your global ambitions.

Get the best of both worlds at LILT! Dive into dynamic in-office energy 2 days a week, sparking creativity and forging bonds with your awesome team. Then, seamlessly shift gears and crush your to-do list from the comfort of your home base for the rest of the week. It's the perfect harmony of productivity and personal freedom. Want a peek inside? Visit our Careers page!

Authorization to work in the U.S. is a precondition of employment.

The Engineering Team at Lilt

Lilt is a high-performance, large-scale language translation system. We invest in and prioritize workflow (i.e., usability and interface design) and backend AI systems. Since the translation workforce is distributed worldwide, there are interesting cloud engineering problems to solve. We have a strong preference for building our own backend technology, so you’ll be implementing and working with the latest natural language processing (NLP) techniques and ideas.

The Engineering Team at Lilt

Lilt is a high-performance, large-scale language translation system. We invest in and prioritize workflow (i.e., usability and interface design) and backend AI systems. Since the translation workforce is distributed worldwide, there are interesting cloud engineering problems to solve. We have a strong preference for building our own backend technology, so you’ll be implementing and working with the latest natural language processing (NLP) techniques and ideas.

Where you'll work:

Work from home allowed up to 3x/wk (within reasonable commuting distance to Emeryville, CA).

This position is eligible for Lilt’s Employee Referral Program.

The Staff ML Engineer (Data Processing & Deployment) will apply knowledge of computer and

information science to perform the following tasks, dividing time according to the approximate

percentages set out below.

What you'll Do:

Product and Engineering (50%)

• Develop and train state-of-art production-level Machine Translation models to be used by

both LILT customers and translators.

• Develop and maintain a collection of services (Python, Java) to query and transform the

customer data for the purpose of adaptation experiments, including but not limited to on-

the-fly identification of outliers which can negatively impact fine-tuning performance.

• Contribute to engineering and product planning meetings to suggest and discuss

improvements to the LILT machine-learning ecosystem.

• Develop automated systems to create the best possible processes for production-level

deployment of Machine Learning models (Kubernetes and Helm) to provide well

documented instructions for production-quality releases and A/B testing.

• Identify performance bottlenecks and usability improvements in the research and

development infrastructure and propose and lead improvements to replace or upgrade it

with updated, more efficient, and better performing libraries and tools.

• Keep up to date with libraries and technologies in the field of data caching (Redis),

messaging systems (RabbitMQ, PubSub), databases (MySQL), and continuous

improvement (Jenkins), to engineer the best possible product to service quality

translations.

Research and Innovation (30%)

• Keep up to date on the latest research in Machine Translation, Large Language Models,

and similar fields. This involves reading and curating research papers and presenting

solutions or improvements to either our product