Senior ML Evaluation Engineer for Voice AI

Jobot; New York (NY); On-site; USD 200,000 - 300,000; Full time

Job summary

Jobot is seeking a Machine Learning Engineer to build out the evaluation foundation for AI voice agents and related products. You will work on voice models, evaluation benchmarks, and LLM-based assessment frameworks to ensure accuracy, latency, and safety in production environments.

The role requires 8+ years of experience, deep ML evaluation expertise, and hands-on model training experience. This is an on-site position in Austin with a strong, diverse team and opportunities for impact across

Qualifications

• Bachelor's degree in Computer Science, Machine Learning, Statistics, or a related field.
• 8+ years of overall professional experience, including 3+ years in ML Engineering or Applied ML.
• Strong experience evaluating supervised and unsupervised ML models, LLMs, and deep learning systems.
• Hands-on experience with failure analysis and LLM evaluation.
• Experience building automated evaluation systems.
• Strong communication skills, able to explain complex concepts to technical and non-technical audiences.
• Practical experience training or fine-tuning voice models (TTS, ASR) and building data pipelines.

Responsibilities

• Design and document comprehensive evaluation frameworks for AI agents across voice, chat, and messaging platforms.
• Train and fine-tune voice models (TTS, ASR, and speech-to-speech) using production and synthetic data, iterating on architecture and data.

Skills

Model evaluation

LLM evaluation

Automated evaluation systems

Voice model training

Communication skills

Education

Bachelor's degree in CS/ML/Statistics

Master's or PhD (preferred)

Job description

Jobot is seeking a Machine Learning Engineer to build out the evaluation foundation for AI voice agents and related products. You will work on voice models, evaluation benchmarks, and LLM-based assessment frameworks to ensure accuracy, latency, and safety in production environments.

The role requires 8+ years of experience, deep ML evaluation expertise, and hands-on model training experience. This is an on-site position in Austin with a strong, diverse team and opportunities for impact across