Offer summary

Qualifications:

Degree in Computer Science or related field preferred, 5+ years of experience in data pipelines, Expertise in NLU/ASR algorithms, Proficient in Python and AI/ML frameworks, Knowledge of probability, statistics, and algorithms.

Key responsabilities:

Create data processing and analysis pipelines

Drive data-driven decision-making with analytics

Develop scalable AI/ML training pipelines

Participate in novel algorithm development for NLU/ASR

Analyze and improve AI model performance

Job description

This is a remote position.

Our main product is innovative, conversational voice-based AI for the hospitality industry.
A thorough understanding of drive-through voice orders requires deep technical knowledge. To tackle this big challenge, we're building our own Speech Recognition and Natural Language Understanding stack from the ground up

In This Role You Will:

Create pipelines to process and analyze our vast data sources. Create tools to uncover and visualize the patterns hidden in the data.
Drive data-driven decision-making by leveraging data analytics and visualization tools.
Develop scalable AI/ML pipelines for training SOTA/NLU models
Participate in the development of novel algorithms for specific problems in our NLU / ASR domain, focusing on noisy input.
Analyze and improve AI model performance.
Own major parts of the NLU / ASR tech that are directly used in production.

Requirements

A degree in Computer Science, Data Science, Machine Learning, or a related field is preferred. Advanced degrees are a plus.
Expertise in creating novel algorithms, especially for handling noisy input data in the NLU/ASR domain.
At least 5 years of proven experience in designing and implementing data pipelines for large-scale data processing and analysis using Python.
Proficiency in programming languages commonly used in AI/ML, such as Python, and familiarity with frameworks like TensorFlow, PyTorch, or similar.
Knowledge of probability and statistics, design, data structures, and algorithms
Excelling at problem-solving with an adaptable and versatile startup mindset
Industry experience with GIT