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 LiltLilt 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.
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 or the overall stack of Machine Translation knowledge and Large Language Models, and data preparation for human-preference alignment.Identify and develop proof of concept solutions, such as domain adaptation, AI-driven quality measurement, for large scale Natural Language processing systems to bridge the gap between the performance of LILT and publicly or privately available Artificial Intelligence models and systems, such as GPT-4, Google Translate, and Amazon Translate.Iterate and develop the best possible architecture for Multilingual Machine Translation and Creation models to be deployed to LILT's production environment, while not compromising on performance.Identify and experiment with methods to improve the processes for large-scale data processing for ML model training (reference free COMET based filtering, ROUGE, Creative Writing), to allow for faster training turnaround times while not compromising quality or performance.Repeatedly demonstrate good judgment in driving applied research initiatives within LILT that lead to the highest possible impact for customers and internal teams.Keep up to date with libraries and frameworks to interact with and design neural networks (Tensorflow, Pytorch, and NVIDIA NeMo).Submit the process and results of research projects to peer-reviewed conferences and publications (ACL, EMNLP, NAACL).Serve as Machine Translation Spokesperson (20%)Be the spokesperson for Machine Learning applied research initiatives being conducted both internally and externally LILT. Effectively train non-technical teams (including but not limited to Production, Marketing and Sales) on complex research ideas.Develop graphical tools and methods to enable customer-facing organizations to explain observed phenomena in Language models to customers.Minimum Requirements:Master's degree in computer science, statistics, computational math/linguistics, machine learning, or related technical field.5 years of experience building large-scale Natural Language Processing systems using Machine Translation (MT) models.Willing to accept any reasonable combination of education and experience (B.S. + 7 yrs of exp or Ph.D. + 3 yrs of exp).Experience using Tensorflow or PyTorch to interact with and design neural networks – 5 years.Experience with Python – 5 years.Experience using Nvidia NeMo to design large language models – 2 years.Large-Scale Data Processing experience for ML Model Training – 4 years.Experience with Production-Level Deployment of Machine Learning Models– 4 years, including at least 3 years using Kubernetes.Apply online at https://lilt.com/careers or submit resume to Lilt, Joern Wuebker, 2200 Powell St., Ste. 900, Emeryville, CA 94608.
Our Story Our founders, Spence and John met at Google working on Google Translate. As researchers at Stanford and Berkeley, they both worked on language technology to make information accessible to everyone. They were amazed to learn that Google Translate wasn't used for enterprise products and services inside the company and left to start a new company to address this need – Lilt.
At its core, Lilt has always been a machine learning company since its incorporation on March 6, 2015. At the time, machine translation didn't meet the quality standard for enterprise translations, so Lilt assembled a cutting-edge research team tasked with closing that gap. While meeting customer demand for translation services, Lilt has prioritized investments in Large Language Models, believing that this foundation was imperative to the future of enterprise translation.
Benefits: Compensation: Competitive salary, meaningful equity, and time off plus company holidays.Monthly lifestyle benefit stipend via the Fringe platform to allow employees to customize benefits to their lifestyle.US Benefits: Compensation: At market salary meaningful equity, 401(k) matching, and flexible time off plus company holidays.Medical Benefits: Employees receive coverage of medical, dental, and vision insurance, plus FSA/DFSA, HSA, and Commuter benefits. In addition, LILT pays for basic life insurance, short-term disability, and long-term disability.Paid parental leave is provided after 6 months.Monthly lifestyle benefit stipend via the Fringe platform to allow employees to customize benefits to their lifestyle.Lilt is an equal opportunity employer. We extend equal opportunity to all individuals without regard to an individual's race, religion, color, national origin, ancestry, sex, sexual orientation, gender identity, age, physical or mental disability, medical condition, genetic characteristics, veteran or marital status, pregnancy, or any other classification protected by applicable local, state or federal laws. We are committed to the principles of fair employment and the elimination of all discriminatory practices.

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