What You'll Do
- Lead research efforts in machine learning for agentic flows, with a focus on speech/audio understanding and decision-making.
- Explore, design, and evaluate state-of-the-art methods, running rigorous benchmarks and experiments.
- Translate research outcomes into robust, production-ready solutions in collaboration with engineering and product teams.
- Define metrics, measurements, and error analysis frameworks to ensure robustness and reliability in production.
- Monitor deployed models, analyze performance regressions, and drive continuous improvements in accuracy and efficiency.
- Act as the team’s primary research authority, staying up to date with the latest advances in ML, deep learning, and speech/audio processing, and applying them to our platform.
What We’re Looking For
- 5–7+ years of hands-on experience in data science and applied machine learning.
- Strong background in both classical ML techniques and modern deep learning methods.
- Proven experience deploying, monitoring, and iterating on models in production.
- Experience designing and executing rigorous experiments, benchmarks, and error analyses.
- Familiarity with agentic or sequential-flow systems (multi-step decision making, fallback logic, orchestration).
- Proficiency in Python and ML/DL frameworks (e.g. PyTorch, TensorFlow, scikit-learn).
- Strong problem-solving skills, curiosity, and ability to learn quickly.
- Great collaborator who values ownership, autonomy, and teamwork.
- Experience working in a fast-growing startup, with the ability to operate in a dynamic, fast-paced environment.
- Bonus: prior work with speech/audio signals (e.g. ASR, embeddings, signal processing).
Candidate Privacy Notice