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.
Authorization to work in the U.S. / Germany 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.
What you’ll do
In tight collaboration with Lilt’s research team, the infrastructure team, and the wider Engineering organization you will be in charge of productizing new AI technologies, improving and maintaining our Machine Learning Operations infrastructure, and optimizing Large Language Model deployments.
Key Responsibilities:
- Design, maintain and optimize CI/CD pipeline and infrastructure for Large Language Model and vector database deployments.
- Collaborate with the Research and Engineering teams on infrastructure development for Lilt’s production and on-premise environments.
- Design and implement architecture to efficiently productize new AI technologies, guaranteeing high availability and reliability.
- Identify and facilitate delivery of multi-team projects on clear timelines.
- Give constructive, effective technical and organizational feedback on work product and communication.
- Work with Product to prioritize infrastructure improvements and technical debt against business requirements.
Skills and Experience:
- Bachelor’s, Master’s or equivalent in Computer Science, Statistics, or Computational Math (or equivalent industry experience in Computer Science or a related technical discipline).
- 3+ years of engineering experience.
- 2+ years experience working on a Machine Learning product.
- Experience with containerized CI/CD workflows.
- Experience with production deployment and optimization of large neural networks on accelerator hardware (GPUs).
- Experience with distributed LLM training infrastructures.
- Excellent verbal and written communication skills.
- Passion to devise solutions that require a focus on systems thinking.
- Demonstrated ability to gather, organize, and synthesize significant and diverse information.
- Strong desire to master the product that you create, and to understand the customer that uses the product.
- Experience collaborating with other engineers and researchers on large-scale machine learning systems.
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.
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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