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    Staff Data Engineer, Data Platform - Boston, United States - Lilt

    Lilt
    Lilt Boston, United States

    1 week ago

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    Description

    Job Description

    Job Description

    STAFF DATA 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

    Where you'll work

    This position can be based out of our Indianapolis, IN office and will be expected to work in the office in a hybrid capacity. Additional locations include the Washington D.C., New York City, and Boston metropolitan areas where you will start as fully remote and then transition to hybrid once offices are opened in those locations.

    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.

    What you'll do

    In collaboration with the Director of Engineering, the Staff Data Engineer will own the scaling and modernization of our data infrastructure to improve reliability and performance, and will collaborate on AI engineering projects to improve our AI data pipelines, product, and services. The Staff Data Engineer will also be charged with team lead responsibilities and will play a big part in roadmap definition and execution.

    Key Responsibilities:

    • Design and implement event-driven and fault-tolerant systems to improve Lilt's data infrastructure, providing timely and reliable data to all areas of the business
    • Apply your engineering experience to implement new data products and services to enable both internal and external customers
    • Design and lead data team projects
    • Share your knowledge with your colleagues, helping them to grow their technical skills
    • Keep the technical excellence bar high, contributing to code quality, doing code reviews, increasing test coverage, etc.
    • Partner with product team and help to decompose huge business requirements into smaller deliverables

    Skills and Experience:

    • 5-10 years of software development experience with two or more general purpose programming languages including, but not limited to, Java and Python
    • Great problem solving abilities
    • Interest in AI technologies
    • Working proficiency in English
    • Must have 4 years experience with Apache Kafka, Presto, and/or NoSQL datastores
    • 2 years of experience architecting data systems
    • Prefer knowledge in Apache Hadoop, BigQuery, and/or BigTable

    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: 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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