Speech Recognition Engineer
Impact: Accessibility and voice interface quality for millions of users
Build and optimize automatic speech recognition systems that convert spoken audio to text with high accuracy across accents, languages, and acoustic environments. Design acoustic models, language models, and end-to-end neural ASR pipelines.
What the day looks like
- People interaction
- Minimal
- Team vs solo
- 50% Team / 50% Solo
- Client facing
- Rarely
- Impact visibility
- Moderate
- Travel
- Minimal
- Schedule flexibility
- Flexible
- Remote work
- Mostly Remote
- Typical work hours
- 40 to 50 hours/week
- Stress level
- Moderate
At a glance
- Median salary
- $155,000
- Entry-level
- $110,000 - $135,000
- Senior
- $200,000+
- Growth by 2033
- 22% (faster than average)
- Demand
- Growing Fast
- Freelance potential
- Low
- Salary growth potential
- High - 60 to 80% growth from entry to senior
- Typical student debt
- $30,000 - $80,000
Skills you'll use
Hard skills
- PyTorch
- Kaldi
- ESPnet
- Whisper
- Python
- Signal processing
- Transformer architectures
Soft skills
- Analytical thinking
- Attention to detail
- Intellectual curiosity
- Persistence
- Problem-solving
Technical complexity: Very High
How to get there
- Minimum education
- Master's Degree
- Licensing
- No
- Years to mid-career
- 3 to 5 years
- Years to senior
- 7 to 10 years
- Career switching
- Hard
Where this career leads
How people arrive here
Where you can go from here
Typical progression
- ML Engineer > Speech Recognition Engineer > Senior Speech Engineer > Staff Speech Scientist > Principal Scientist
Future outlook
- Automation probability
- 12% low risk as the role creates the speech AI that others use
- AI disruption risk
- Moderate
- Demand trend
- Growing Fast
How people feel about it
- Overall satisfaction
- 7.8/10
- Meaning
- 7.9/10
- Work-life balance
- 7.2/10
- Prestige
- 7.8/10
- Social perception
- High