Senior Data Scientist - NLP/Deep Learning

Description :

- Own end-to-end model development - from requirement gathering and algorithm design to implementation and deployment, you'll shepherd ML features through their complete lifecycle.

- Build for conversational intelligence - develop models that can handle hundreds of thousands of conversations per day with high accuracy and natural language understanding.

- Innovate through research - stay current with cutting-edge NLP and speech technologies, read research papers, and implement state-of-the-art solutions that give us a competitive edge.

- Design ML pipelines - create a robust, scalable machine learning infrastructure that can continuously improve from our growing conversation data.

- Optimize for performance - identify and resolve model bottlenecks to ensure our voice AI delivers natural, real-time conversations without comprehension issues.

Requirements :

- 5+ years of experience in data science, machine learning, or a related field.

- Strong background in natural language processing (NLP) and conversational AI systems.

- Experience with speech recognition and text-to-speech technologies.

- Proficiency in Python and data science libraries (NumPy, Pandas, scikit-learn).

- Familiarity with deep learning frameworks (PyTorch, TensorFlow, Hugging Face).

AI and ML Skills :

- Experience fine-tuning language models (LLMs) for specific domains or tasks.

- Expertise in analyzing conversational data at scale and extracting actionable insights.

- Knowledge of customer intelligence systems and experience building data-driven applications.

- Understanding of speech-to-text optimization and improving transcription accuracy.

Data Engineering and Analytics :

- Experience with large-scale data processing (handling hundreds of thousands of conversations).

- Ability to design and implement data pipelines for continuous model improvement.

- Knowledge of feature engineering techniques for conversational data.

- Experience with A/B testing methodologies to evaluate model improvements.

- Familiarity with data visualization tools for presenting insights to stakeholders.

Startup Mindset :

- You've built and deployed ML models in production environments.

- Comfortable with a fast-paced environment where you'll own critical data science decisions.

- Collaborative approach - you work well with engineering teams, product, and founders.

- Growth-minded and excited about building customer intelligence systems that scale.