Natural Language Understanding

Natural Language Understanding Engineer Jobs

2 jobs found

1mo ago

Machine Learning Engineer, Natural Language Understanding, Proactive

Apple Santa Clara, CA

Santa Clara, CA

1mo ago Closed

$150k - $278k/yr Full time Ai Ml Artificial Intelligence Deep Learning

This position is no longer accepting applications (closed Oct 22, 2026).

Job Description

Build personalized, on-device query understanding that powers search and assistant experiences across Apple products. In Apple’s On-Device Query Understanding team, you will research and deliver machine learning models designed for both quality and efficiency, including LLM/NLU approaches and inference optimization to support fast, power-efficient performance on device.

Work style: Santa Clara, CA (onsite). Compensation: USD 150,400 - 277,600 per year.

What you’ll do

Research, design, implement, and evaluate models that advance personalized query understanding, user intent resolution, retrieval, and ranking
Use natural language processing, deep learning, and large language model techniques to produce grounded, contextually relevant responses
Assess performance gaps in current search and assistant systems, then develop algorithms and techniques to improve model quality and impact key product outcomes
Shape long-term technical direction by defining a vision, proposing roadmaps, and setting measurable objectives
Collaborate with cross-functional partners to define product requirements, establish evaluation metrics, and support outcomes tied to user satisfaction

Requirements

4+ years of experience in machine learning, natural language processing, or computer vision, applied at scale
Production software engineering experience with Python, Go, C/C++, Swift, or Objective-C
Strong communication and collaboration skills
Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, Statistics, Physics, Mathematics, or a related field

Helpful experience

Master’s or Ph.D. in Computer Science, Statistics, or a related field, or equivalent industry experience
Experience with Small Language Models (SLMs) and on-device LLM training, plus model compression/quantization and production deployment
Experience with large-scale query understanding, search, recommendation, or personal assistant systems
Proficiency with ML frameworks such as PyTorch, JAX, TensorFlow, or XGBoost
Background in personalization and data-driven decision making, including the ability to prototype and conduct critical analysis
Experience with Swift, Swift frameworks, or Apple platform development (plus)
Experience with build infrastructure, release management, and CI/CD pipelines (plus)

Technologies you may work with

Large Language Models (LLMs), Natural Language Understanding (NLU), and machine learning inference optimization
PyTorch, JAX, TensorFlow, XGBoost
Small Language Models (SLMs), model compression/quantization
Swift, Objective-C, Python, Go, C/C++

Benefits

Comprehensive medical and dental coverage
Retirement benefits
Discounted products and free services
Reimbursement for certain educational expenses, including tuition
Discretionary bonuses or commission payments and relocation may be eligible
Opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs
Eligible for discretionary restricted stock unit awards
Can purchase Apple stock at a discount if voluntarily participating in the Employee Stock Purchase Plan

Learn more about Apple Benefits

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1mo ago

Senior AI Engineer — Conversational Voice AI

SmartAdvocate Remote 🇺🇸 Remote

Remote

1mo ago Closed

$120k - $160k/yr Full time Backend Developer Ai Engineer Artificial Intelligence

This position is no longer accepting applications (closed Sep 29, 2026).

Job Description

SmartAdvocate is seeking a Senior AI Engineer to build and operate enterprise-grade conversational voice AI agents for legal case intake and client calls. The role focuses on production ownership, telephony integrations, and reliable write-back of call results into case files with safety, monitoring, and audit readiness.

Responsibilities

Architect, build, and deploy conversational voice agents that interact with callers, leads, and clients.
Integrate conversational systems with VoIP/SIP and cloud communications platforms including Twilio, Plivo, Amazon Connect, and LiveKit, supporting topologies such as call forwarding, conferencing an agent onto a live call (including onto an SA number), and full number porting so the solution works with any firm phone system.
Address live-call realities such as barge-in and turn-taking, interruptions, poor reception, accents, background noise, and graceful degradation when confidence drops.
Optimize real-time STT, TTS, NLU, and latency budgets; select and tune voices for naturalness.
Design warm transfer and escalation flows, including handing off to a human with full context and identifying high-value or urgent situations for immediate routing.
Build real-time pipelines that transcribe, parse, and structure call conversations to populate case fields, create intake records, update case notes, and trigger downstream workflows automatically.
Record and summarize every call into the case file with clear provenance for any information the agent entered.
Detect the caller’s language and respond in it, with Spanish as the first priority after English.
Design caller identification and authentication before any case information is disclosed, using more than caller ID alone.
Make agent behavior configurable per firm, including operating hours and after-hours coverage, outbound calling windows by callee type and time zone, escalation rules, and voice selection.
Implement guardrails, fallbacks, structured logging, and call/transcript retention that supports audit requirements.
Own the service in production, including latency budgets, monitoring, alerting, failover, and on-call responsibilities, given the availability-critical nature of a law firm’s main phone line.

Requirements

Demonstrable production experience building conversational voice agents integrated with telephony infrastructure such as SIP/RTP, WebRTC, Twilio Media Streams, LiveKit, Deepgram, ElevenLabs, Vapi, Retell, or similar.
Real-time audio pipeline engineering experience including streaming STT and TTS, sub-second response handling, concurrency, and latency profiling under load.
Pipeline engineering experience for extracting structured JSON or database payloads from live audio streams.
Strong Python service development (FastAPI/async or equivalent) and clean REST API design.
Production-ready LLM integration including function/tool calling, structured outputs, prompt and context engineering, and cost and latency tuning.
Experience with event-driven and asynchronous patterns such as queues, background workers, retries, and idempotency.
Ability to evaluate conversational quality systematically through test suites, transcript review, and regression testing when prompts or models change.
Production ownership experience with containerized deployment, CI/CD, monitoring, structured logging, and having personally debugged a live outage.

Technologies

VoIP/SIP, Twilio, Plivo, Amazon Connect, LiveKit
SIP/RTP, WebRTC, Twilio Media Streams
Deepgram, ElevenLabs, Vapi, Retell
STT, TTS, NLU
FastAPI, Python, LLM, JSON, REST API, CI/CD, queues

Benefits

Salary Range: $120,000.00 - $160,000.00 (yearly)
Comprehensive benefits package
401(k) and 401(k) matching
Dental insurance, Health insurance, Health savings account, Vision insurance, Life insurance
Flexible spending account
Paid time off and Parental leave
Reports to the CTO; works closely with the existing AI Architect and AI development team
Location: Remote (US) or Hybrid in Melville NY
Opportunity to lead high-impact AI work on an established platform with real customers and real data

Location and Salary

Location: Remote (remote)

Salary: USD 120,000 - 160,000 per yearly

How We Hire

Resume and portfolio review
A 45-minute conversation about systems you have built and operated
A short technical exercise using a realistic problem from the actual domain (not a whiteboard puzzle)
A final conversation with the CTO and the AI team

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Natural Language Understanding Engineer Jobs

Machine Learning Engineer, Natural Language Understanding, Proactive

Senior AI Engineer — Conversational Voice AI

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