AI Phone - Applied ML / Model Engineer
BJAK (company site, opens in a new tab)On-siteDirect career pageEst. 12–25 LPA
Posted 19h ago
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Job description
Structured overview of role & requirements
About This Role
- Evaluate and improve foundation models for AI phone use cases, focusing on intent recognition, instruction following, tool calling, and multi-step task execution.
- Conduct model fine-tuning (e.g. SFT, LoRA/QLoRA) and experiment with synthetic data generation to enhance phone-specific workflows.
- Build benchmarks and evaluation datasets, collaborate with the Agent Runtime team to optimize model performance in real-world agent workflows.
Minimum Requirements
- Strong background in Machine Learning, Deep Learning, or NLP.
- Practical experience working with LLMs and open-weight models.
- Experience with model fine-tuning techniques such as SFT, LoRA/QLoRA; preferably RL or preference optimization.
- Experience with PyTorch, ML tooling, LLM evaluation, benchmarking, and dataset preparation.
Ideal Candidate Profile
- Experienced in hands-on ML model experimentation and iterative performance improvement with large language models.
- Able to manage end-to-end model evaluation, dataset construction, and fine-tuning specific to conversational AI and phone workflow applications.
- Comfortable working closely with engineering teams to integrate models into agent workflows, balancing local and cloud model inference considerations.