O
San Francisco, California, United States· Full-time· Remote
$342K – $399K/yr
PythonMachine LearningArtificial IntelligenceAI
L
Active1mo ago
Machine Learning Engineer (Real-Time Speech Translation)
Pay vs market · Bottom quarter
This job's pay ($140,717 a year at the midpoint) is lower than over 90% of 131 salary-listed Machine Learning Engineer jobs in United States in the last 12 months; their median is $248,820.
Role overview
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 , Canva , the United States Department of Defense , the United States Air Force , ASICS , and hundreds of global Enterprises. Backed by Sequoia, Intel Capita
…About this listing
- Source: LILT's official careers site (via Ashby) · last confirmed on the source 3 Nov 2026
- Posted 2 Oct 2026
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Role market pulse
How Machine Learning Engineer demand looks in United States
Live jobs
171
Posted 30d
60
30d movement
+9.1%
Remote share
36.8%
Salary listed
83%
Salary trend 1Y
Not enough history
What they are looking for
Skills & requirements
python →docker →kubernetes →machine learning →artificial intelligence →ai →salesforce →recruitment →
Qualification
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 driv
Department · Engineering
Hiring company
LILT
Technology
Streamline global translation with AI. Connect systems, reduce costs, and secure multilingual content with enterprise-grade workflows.
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