--- title: 'Machine Learning Engineer (Real-Time Speech Translation) at LILT' canonical: 'https://feeny.ai/job/machine-learning-engineer-real-time-speech-translation-lilt-washington-y3qsmhgkpkye' type: 'job' last_seen: '2026-10-14' --- # Machine Learning Engineer (Real-Time Speech Translation) at LILT - **Company:** LILT - **Location:** Washington, DC - **Compensation:** $120k–$161k - **Employment:** full-time - **Work type:** hybrid - **Posted:** 2026-10-02 - **Last confirmed live:** 2026-10-14 - **Apply:** https://jobs.ashbyhq.com/lilt-corporate/0e486151-fd82-4c37-bec1-813270900f64 ## Job description ## About LILT AI is changing how the world communicates — and LILT is leading that transformation. We're on a mission to make the world's information accessible to everyone, regardless of the language they speak. We use cutting-edge AI, machine translation, and human-in-the-loop expertise to translate content faster, more accurately, and more cost-effectively without compromising on brand, voice, or quality. At LILT, we empower our teammates with leading tools, global collaboration, and growth opportunities to do their best work. Our company virtues—Work together, win together; Find a way or make one; Dance in the customer's shoes; Quicker than they expect; Quality is Job 1—guide everything we do. We are trusted by[Intel Corporation](https://www.linkedin.com/company/intel-corporation/),[Canva](https://www.linkedin.com/company/canva/), the[United States Department of Defense](https://www.linkedin.com/company/deptofdefense/), the[United States Air Force](https://www.linkedin.com/company/united-states-air-force/),[ASICS](https://www.linkedin.com/company/asics/), and hundreds of global Enterprises. Backed by Sequoia, Intel Capital, and Redpoint, we’re building a category-defining company in a $50B+ global translation market being redefined by AI. ## Role Summary We are building a new live translation product. We are looking for an ML Engineer to build the real-time speech translation backend that powers it. You will own the real-time speech translation backend end-to-end, from live audio input to translated output. You will build on LILT's production model serving platform (Ray Serve on GPU Kubernetes clusters) and our in-house adaptive machine translation models, working closely with the senior architects of that platform and with our language processing researchers. The ASR and MT models exist. Your job is to make them work together as a low-latency streaming system that holds up in production. This is a hands-on backend engineering role for those looking to own a real-time ML system from end to end, supported by expert guidance and a clear product vision. Our team adopts an AI-first approach, leveraging agentic coding and AI-driven PR reviews to accelerate development. We combine this with deep technical expertise, requiring not only expert Python proficiency but also a comprehensive understanding of the entire ML stack, from optimizing neural network architectures to managing production infrastructure on Kubernetes, and making informed, cost-aware decisions on hardware selection. Location & eligibility: This position requires US citizenship and residence in the United States. Preferred locations are Washington, D.C.; Boston, MA; and Indianapolis, IN (East Coast / ET timezone preferred). ## Key Responsibilities - Real-time pipeline architecture: Build and manage services for high-throughput, real-time audio and text streaming. Handle signal processing, session lifecycles, and concurrency management to ensure robust operation under load. - ML model integration: Integrate and serve streaming speech recognition and machine translation models, collaborating with research teams to ensure models operate within required latency budgets. - Quality and confidence workflows: Develop logic for model-based confidence scoring, routing segments for human intervention as needed, and broadcasting real-time updates and corrections to end-users. - Infrastructure and scale: Architect and scale production ML infrastructure on GPU-accelerated Kubernetes clusters. Implement batching, load balancing, and autoscaling strategies to maintain performance and cost-efficiency. - Latency engineering: Establish comprehensive instrumentation for real-time performance. Identify bottlenecks, optimize system throughput, and drive down end-to-end latency metrics to meet production standards. - Interface and API definition: Define technical contracts and interfaces for audio ingestion and downstream service integrations. Partner with frontend and platform engineering teams to maintain clean, robust integration points. - Collaboration and technical leadership: Drive cross-team alignment by defining clear API interfaces and technical contracts, facilitating effective communication between engineering and product teams to ensure seamless system integration. Required Qualifications - BS or MS in Computer Science or a related field, or equivalent practical experience. - 3+ years building production backend or ML serving systems in Python, including strong async programming (asyncio) skills. - Hands-on experience with real-time streaming transport: WebSocket or gRPC bidirectional streaming, session state, backpressure, and connection lifecycle handling. - Experience serving ML models in production on GPUs (Ray Serve, Triton, vLLM, or similar), with Docker and Kubernetes. - Experience integrating speech or NLP models into production systems, ideally streaming ASR (partial hypotheses, endpointing, VAD). - A latency-engineering mindset: you have profiled, instrumented, and optimized a real-time or low-latency system and can reason in per-stage budgets. - Effective use of AI coding agents (Claude Code, Codex, or similar) on top of fundamentals learned the hard way: you let agents do the typing, but you can debug, review, and reason about every line without them, and you know when not to trust them. - US citizenship and residence in the United States (contract requirement). ## Preferred Qualifications - Ray Serve specifically, including streaming responses and model multiplexing. - Familiarity with simultaneous or incremental MT concepts (retranslation, prefix stability, wait-k policies). - Machine translation quality estimation (COMET/CometKiwi class models) or other confidence estimation in production. - Message brokers for real-time fan-out and state distribution (RabbitMQ or similar). - Streaming text-to-speech integration and time-to-first-audio optimization. - WebRTC and SFU concepts, or voice pipeline frameworks (LiveKit Agents, Pipecat). - Handling of CJK and other non-Latin text in NLP pipelines (our first languages are Japanese, Korean, and English). - Observability tooling (Datadog, Prometheus) for production ML systems. 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. While together at Google, they were amazed to learn that Google Translate wasn’t used for enterprise products and services inside the company.The quality just wasn’t there. So they set out to build something better. LILT was born. LILT has been a machine learning company since its founding in 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, human-in-the-loop systems, and now agentic AI. With AI innovation accelerating and enterprise demand growing, the next phase of LILT’s journey is just beginning. Our Tech What sets our platform apart: - Brand-aware AI that learns your voice, tone, and terminology to ensure every translation is accurate and consistent - Agentic AI workflows that automate the entire translation process from content ingestion to quality review to publishing - 100+ native integrations with systems like Adobe Experience Manager, Webflow, Salesforce, GitHub, and Google Drive to simplify content translation - Human-in-the-loop reviews via our global network of professional linguists, for high-impact content that requires expert review LILT in the News - Featured in [The Software Report’s](https://www.thesoftwarereport.com/the-top-100-software-companies-of-2024/) Top 100 Software Companies! - LILT makes it onto the [Inc. 5000 List](https://labs.lilt.com/lilt-listed-on-the-2024-inc-5000). - LILT’s continues to be an intellectual powerhouse, holding [numerous patents](https://patents.justia.com/inventor/john-sturdy-denero) that help power the most efficient and sophisticated AI and language models in the industry. - Check out [all our news on our website](https://lilt.com/news). Information collected and processed as part of your application process, including any job applications you choose to submit, is subject to LILT's Privacy Policy at https://lilt.com/legal/privacy. At LILT, we are committed to a fair, inclusive, and transparent hiring process. As part of our recruitment efforts, we may use artificial intelligence (AI) and automated tools to assist in the evaluation of applications, including résumé screening, assessment scoring, and interview analysis. These tools are designed to support human decision-making and help us identify qualified candidates efficiently and objectively. All final hiring decisions are made by people. If you have any concerns, require accommodations, or would like to opt-out of the use of AI in our hiring process, please let us know at recruiting@lilt.com. 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. ## About LILT ## Company Overview - **One-liner**: LILT provides an enterprise AI translation platform that combines custom and bring-your-own AI models with human domain experts to enable multilingual content production at scale. - **Entity Type**: Private (Series C, $140M+ total funding) - **Headquarters**: San Francisco, California, United States - **Founded**: March 2015 - **Founders**: Spence Green (Co-founder & CEO), John DeNero (Co-founder & Chief Scientist) ## Core Business - Primary industry/industries: Enterprise AI Translation, Localization, Language Technology, Agentic AI - Target customers: B2B – large enterprises, public sector / government, and AI/ML teams (Fortune 100, U.S. Department of Defense, Intel, Lenovo, Canva, National Weather Service) - Mission or purpose statement: “Make the world’s information available to everyone, no matter the language they speak.” ## Products & Services - **LILT Contextual AI Platform**: End-to-end platform for training custom translation models, automating workflows, and ensuring quality. Supports BYO AI models (Gemini, GPT, Claude, etc.) and integrates with 100+ business systems via API/MCP. - **Agentic AI Translation**: Autonomous agents that handle multilingual content for product launches, technical documentation, regulatory compliance, marketing campaigns, and critical public service alerts. - **Domain Expert Network**: 40+ specialized domains (legal, medical, tech, etc.) with human experts (not freelance) to verify and enhance AI output, ensuring brand consistency and accuracy. - **Enterprise Governance & Analytics**: Real-time admin tools for workflow management, user permissions, budgets, and program data – deployed in on-premise, air-gapped, and multi-cloud environments. - **Security Certifications**: SOC 2® Type II, ISO 9001, ISO 17100; trusted by regulated industries (financial services, healthcare, defense). ## Market Standing - **Valuation / Funding**: $140M+ total funding (as of Series C); valuation not publicly disclosed - **Key Metric**: Total funding amount ($140M+) – revenue is not publicly available (private company) - **Notable Investors / Partners**: Backed by leading AI, ML, NLP, and enterprise software investors (specific names not listed in provided sources). Partners include Intel, Lenovo, Canva, U.S. Department of Defense, National Weather Service. - **Growth Signals**: Cost reduction of 40–50% for customers (Intel, Canva); 60% faster delivery timelines (Lenovo); 25M+ people receiving life-saving weather alerts; 100+ languages supported; continuous hiring across AI research, engineering, and operations. ## Competitive Advantages - **PhD-led AI research team** with over a decade of focus on multilingual generative AI and Large Language Models (founded by former Google Translate researchers from Stanford/Berkeley). - **Continuous model improvement** via real-time human-AI interaction retraining, ensuring the system gets smarter with every translation. - **Defense-grade trust & enterprise governance** – deployed in air-gapped/on-premise environments for the most security-conscious organizations (DoD, Fortune 100). - **Specialized human expertise** across 40+ domains – not just general freelancers – ensuring accuracy for regulated and technical content. - **100+ native integrations** and multi-cloud support, enabling self-serve scaling without operational burden. ## Strategic Focus - **Agentic AI for multilingual use cases** – expanding autonomous agents that can handle end-to-end localization workflows. - **AI model customization & interoperability** – enabling enterprises to bring their own models (BYO AI) and to evaluate/audit agent performance. - **Continued investment in generative LLMs** as the foundation for enterprise translation, with a focus on quality, compliance, and speed. - **Public sector growth** – delivering critical public service information faster through agentic AI. ## Why Work Here - **Culture & Values**: “Quality is Job #1”, “Work Together, Win Together”, “Find a Way or Make One”, “Dance in the Customer’s Shoes”, “Quicker Than Expected”. - **Work Policy**: Headquarters in San Francisco with offices worldwide; flexible/remote options implied by “Global by Design” and “Flexible Time Off”. - **Benefits**: - Full healthcare coverage (medical, dental, vision) - 401K matching (U.S.) - Competitive compensation + top-market equity - Flexible Time Off and Parental Leave - Professional development via LILT University (activities cultivating learning, knowledge, growth) - **Engineering / AI Culture**: Opportunity to work on frontier multilingual AI with a PhD-led research team; roles posted include AI Researcher / ML Engineer (ASR & Speech Specialist) across multiple U.S. cities. ## Sources 1. [lilt.com – About LILT](https://lilt.com/company) 2. [lilt.com – Enterprise AI Translation Platform](https://lilt.com/) 3. [lilt.com – Careers](https://lilt.com/careers) 4. [jobs.ashbyhq.com – LILT Jobs](https://jobs.ashbyhq.com/lilt-corporate) 5. [linkedin.com – LILT AI](https://www.linkedin.com/company/lilthq) ## Other roles at LILT - [Data Engineering Manager](https://feeny.ai/job/data-engineering-manager-lilt-indianapolis-5gg9cnc20cry) — Indianapolis, IN - [Technical Project Manager, Applied AI (Contract)](https://feeny.ai/job/technical-project-manager-applied-ai-contract-lilt-london-65tnpf6z9xr7) — London, United Kingdom - [Staff Fullstack Engineer - Internal Tools](https://feeny.ai/job/staff-fullstack-engineer-internal-tools-lilt-united-states-t32rgc1brnc3) — United States - [Enterprise Account Executive](https://feeny.ai/job/enterprise-account-executive-lilt-london-bemg05h1jcm9) — London, United Kingdom - [Enterprise Account Executive](https://feeny.ai/job/enterprise-account-executive-lilt-boston-7z9fca3354z0) — Boston, MA - [Senior Full Stack Engineer](https://feeny.ai/job/senior-full-stack-engineer-lilt-washington-b78y6bhxvv28) — Washington, DC - [Backend Engineer](https://feeny.ai/job/backend-engineer-lilt-washington-2wx2hmgrnz4r) — Washington, DC - [Senior Technical Program Manager, Applied AI](https://feeny.ai/job/senior-technical-program-manager-applied-ai-lilt-sydney-7pzecekfc63r) — Sydney, Australia - [Senior Technical Product Manager, Connectors](https://feeny.ai/job/senior-technical-product-manager-connectors-lilt-new-york-5hjk35jpanrg) — New York, NY - [Project Manager, Applied AI](https://feeny.ai/job/project-manager-applied-ai-lilt-united-states-8q23nk08ahzn) — United States