Automotive Voice AI Jobs

Build the future of in-car voice interfaces. Hands-free navigation, climate control, entertainment—all powered by noise-robust ASR and natural dialogue.

AI Engineer, Embodied Intelligence, Optimus

Tesla

$140,000 - $420,000 LOCATION TBD NUMPY / DIARIZATION / EMOTION

The Role

Tesla is building robust embodied intelligence through autonomous driving and humanoid robots. Core to reaching this goal is developing intelligent agents that see, move, and speak in the real world. In this role, you’ll architect and deploy models that allow our agents to listen, understand, and respond in real time powered by our custom AI chip on our embodied products. Your…

Requirements

Strong software engineering practices and is very comfortable with Python and Numpy programming, debugging/profiling, and version control
Experience with speech-related machine learning tasks: ASR, emotion detection, speaker diarization, or multimodal input processing
Experience training and fine-tuning large-scale speech models, LLMs, or VLMs

Apply directly

This role is open at the company now — apply on their careers page.

Apply on company site →

Open Positions

$155K-$250K

Average Salary

65%

New Cars w/ Voice (2026)

Why Automotive Voice AI?

Voice interfaces are becoming standard in vehicles as drivers demand safer, hands-free control. Modern cars are software-defined vehicles with advanced infotainment systems, and voice AI is the primary interface for navigation, climate, media, and increasingly, autonomous vehicle features.

The automotive voice market is unique because:

Extreme noise conditions: Highway speeds (80+ dB), music, passenger conversations, engine noise
Safety-critical: Distracting the driver is dangerous; accuracy and low latency are paramount
Edge deployment: Processing must happen on-device for privacy and offline functionality
Long product cycles: Cars last 10+ years; software must be robust and updatable
Global markets: Support for 50+ languages with regional accents

Automotive ASR Challenges

Key Technical Hurdles: Road noise (70-90 dB) obscures speech. Far-field microphones (1-2m from driver). Competing audio sources (music, GPS). Limited compute (embedded chips). Must work offline (tunnels, rural areas). Latency <500ms for natural interaction.

What You'll Work On

Noise-robust ASR: Deep learning models trained on in-car noise profiles, beamforming, acoustic echo cancellation
Wake word detection: "Hey Mercedes," "Hey BMW"—ultra-low power, always-on listening
Natural dialogue: Multi-turn conversations for complex tasks like route planning with waypoints
Contextual understanding: "Make it warmer" → increase cabin temp; "Call Mom" → initiate call to contact
On-device inference: Model compression for real-time ASR on automotive SoCs (Snapdragon, NVIDIA DRIVE)
Safety integration: Driver monitoring, distraction detection, emergency command handling

Major Use Cases

Hands-Free Controls

Core infotainment control via voice commands.

Navigation: "Navigate to nearest gas station"
Climate: "Set temperature to 72 degrees"
Media: "Play my workout playlist"
Phone: "Call Sarah on speakerphone"

AI Assistants

Branded in-car assistants with personality.

Mercedes MBUX
BMW Intelligent Personal Assistant
Tesla Voice Commands
Rivian Alexa integration

Advanced Driver Assistance

Voice for semi-autonomous features.

"Activate lane centering"
"What's my estimated range?"
"Find charging stations along route"
Voice feedback for autonomous driving status

Third-Party Integration

Connecting car to broader ecosystems.

Apple CarPlay / Siri integration
Android Auto / Google Assistant
Amazon Alexa Auto
Smart home control from car

Companies hiring for automotive voice AI roles

These companies build in this space and hire for automotive voice AI work. Specific openings come and go — check their careers pages, and get the current ones each week in the SpeechTechJobs digest.

Tesla — in-vehicle voice control and driver-assistance UX
Rivian — EV in-cabin experience and voice interaction
Mercedes-Benz — the MBUX in-car voice assistant
General Motors — in-vehicle infotainment and voice
SoundHound AI — a voice-AI platform used by automakers

Get automotive voice AI roles weekly

New ASR, TTS, voice-AI and speech-analytics roles from ~30 companies, plus salary and hiring notes. One email a week, free.

Required Skills & Qualifications

Core Technical Skills

ASR fundamentals: Experience with Whisper, Kaldi, or custom architectures
Noise robustness: Beamforming, acoustic echo cancellation, speech enhancement
Edge AI: Model quantization, pruning, distillation for embedded deployment
Programming: C++ (production systems), Python (prototyping, training)
Audio processing: Signal processing, microphone arrays, far-field capture

Automotive-Specific Knowledge

Automotive SoCs: Qualcomm Snapdragon Auto, NVIDIA DRIVE, NXP i.MX
Safety standards: ISO 26262 (functional safety), ASPICE
Automotive protocols: CAN bus, AUTOSAR, Vehicle APIs
Infotainment systems: Android Automotive, QNX, Linux-based systems
OEM processes: Long development cycles (2-4 years), extensive testing

Desirable Experience

Prior work in automotive, consumer electronics, or IoT
Wake word detection systems (always-on listening)
Dialogue system design for hands-free scenarios
Multilingual ASR (especially European and Asian languages)
Experience with Tier 1 suppliers (Bosch, Continental, Harman)

Education

Minimum: BS in CS, EE, or related field
Preferred: MS in speech processing, signal processing, or ML
Alternative: BS + 3+ years automotive voice AI experience