Remote Staff ML Engineer

Summary

Join our team at Lilt as a Staff ML Engineer (Data Processing & Deployment) and contribute to building high-performance, large-scale language translation systems. You will work on developing state-of-art production-level Machine Translation models, maintaining services for customer data adaptation experiments, and contributing to engineering and product planning meetings.

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

Responsibilities

• 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: 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
• Research and Innovation: 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
• Research and Innovation: 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
• Research and Innovation: 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
• Research and Innovation: Repeatedly demonstrate good judgment in driving applied research initiatives within LILT that lead to the highest possible impact for customers and internal teams
• Research and Innovation: Keep up to date with libraries and frameworks to interact with and design neural networks (Tensorflow, Pytorch, and NVIDIA NeMo)
• Serve as Machine Translation Spokesperson: Be the spokesperson for Machine Learning applied research initiatives being conducted both internally and externally LILT
• Serve as Machine Translation Spokesperson: Effectively train non-technical teams (including but not limited to Production, Marketing and Sales) on complex research ideas
• Serve as Machine Translation Spokesperson: Develop graphical tools and methods to enable customer-facing organizations to explain observed phenomena in Language models to customers

Benefits

• Competitive salary
• Meaningful equity
• Time off plus company holidays
• Monthly lifestyle benefit stipend via the Fringe platform to allow employees to customize benefits to their lifestyle
• US Benefits: At market salary meaningful equity, 401(k) matching, and flexible time off plus company holidays
• US Benefits: Medical Benefits: Employees receive coverage of medical, dental, and vision insurance, plus FSA/DFSA, HSA, and Commuter benefits
• US Benefits: Lilt pays for basic life insurance, short-term disability, and long-term disability
• Paid parental leave is provided after 6 months