AI Phone - Applied ML / Model Engineer

The role

This person will evaluate foundation models against target phone use cases. They will perform model adaptation, fine-tuning, and build evaluation datasets to improve model performance for agent workflows.

What you will do

• Evaluate existing foundation models against target phone use cases.
• Identify capabilities for existing models and where adaptation or fine-tuning is needed.
• Experiment with SFT, LoRA/QLoRA and other lightweight fine-tuning techniques.
• Improve model performance for intent recognition, instruction following, tool calling, structured outputs, and multi-step task execution.
• Explore synthetic data generation and dataset construction for phone-specific workflows.
• Build evaluation datasets and benchmarks to measure model quality, reliability, and task completion.
• Compare different models and approaches, including local versus cloud inference.
• Work closely with the Agent Runtime team to improve model performance in actual agent workflows.

Required qualifications

• Strong background in Machine Learning, Deep Learning, or NLP.
• Practical experience working with LLMs and open-weight models.
• Experience with model fine-tuning, such as SFT, LoRA/QLoRA.
• Experience with PyTorch and common ML tooling.
• Understanding of LLM evaluation, benchmarking, and dataset preparation.
• Ability to run experiments, analyze model failures, and translate findings into measurable improvements.

Nice to have

• Experience with RL or preference optimization.
• Experience with agentic systems, function calling, and tool-use training.
• Experience with synthetic data generation and preference datasets.
• Experience with model distillation and smaller language models.
• Experience with deploying models in production environments.

About the company

bjakcareer aims to build proactive applications and devices that bring intelligence into daily conversations, coordination and workflows.