AI Research Engineer - Speech & Audio AI | Duolingo

As an AI Research Engineer on the Speech team, you will join a full-stack engineering environment dedicated to developing, training, and deploying custom speech and audio models. The Speech team builds state-of-the-art models that understand non-native learners' speech, powering flagship interactive features such as Video Call and the core learning path. Working across all layers of the ML stack—from feature engineering and training data creation to fine-tuning, reinforcement learning, evaluation benchmarks, and production deployment—you will combine cutting-edge AI research with engineering implementation to deliver scalable educational technology.

Key Responsibilities

Speech Modeling & Neural Architecture

• Model Development & Training: Design, train, and fine-tune large-scale neural network models covering automatic speech recognition (ASR), text-to-speech (TTS), speech-to-speech architectures, and audio tokenization.
• Full-Stack ML Lifecycle: Oversee end-to-end machine learning workflows, including dataset generation, feature engineering, RL framework integration, benchmark evaluations, production serving, and continuous monitoring.
• Product Integration: Collaborate with full-stack frontend, backend, and product engineering teams to integrate custom speech models into live product experiences like Video Call and adaptive learning paths.

Leadership & Technical Strategy

• Strategic Direction: Serve as a core member of the Speech leadership group, participating in strategic product and business decision-making to align AI capabilities with company objectives.
• Cross-Functional Alignment: Partner with cross-functional stakeholders to understand domain requirements and tune model outputs for educational efficacy.
• State-of-the-Art Applied Research: Monitor emerging developments across machine learning and speech research, translating new techniques into production improvements.
• Mentorship: Mentor and guide team members, fostering a collaborative culture and supporting their professional growth.

Requirements

Applied AI & Speech Expertise

• AI Research Track Record: Proven background as an AI research engineer with specialized experience in speech recognition (ASR), text-to-speech (TTS), Large Language Models (LLMs), or related audio fields.
• Large Model Fine-Tuning: Hands-on experience training, fine-tuning, and evaluating large-scale neural network models in an applied, production setting.
• Academic Background: Advanced degree (Master's or Ph.D.) in Computer Science, Engineering, Artificial Intelligence, Machine Learning, or equivalent practical experience.
• ML Fundamentals & Best Practices: Deep understanding of modern machine learning concepts, framework ecosystems (PyTorch, TensorFlow), and deployment best practices.
• Leadership & Communication: Outstanding communication, leadership, and collaboration skills, with a track record of driving cross-functional alignment.

Total Rewards & Benefits

• Market-Competitive Compensation: Base salary range of $220,800 – $331,200 USD / year supplemented by equity compensation grants.
• Holistic Wellbeing: Comprehensive health, dental, and vision insurance packages alongside mental health resources.
• Professional Growth: Limitless learning opportunities, continuous mentorship, and collaboration with top-tier AI researchers and engineers.
• Mission-Driven Culture: Impact-focused work environment dedicated to making high-quality global education universally accessible.