ML Engineer: Edge Deployment & Fine-Tuning Expert

Quantiphi; Atlanta (GA); On-site; USD 140,000 - 190,000; Full time

Job summary

Quantiphi is seeking a senior Machine Learning Engineer to join the AI/ML team in Atlanta. You will own model fine-tuning, evaluation, and production deployment for AI agents and models used in industrial use cases. You will collaborate with AI Architects, Data Scientists, and deployment engineers to deliver end-to-end AI solutions.

You will optimize LLM/SLM agent behavior, build data pipelines, and develop benchmarking frameworks to balance accuracy and latency in real-time applications.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science or related.
• 3–7 years of hands-on ML engineering experience (as per job context).
• Experience taking models from experiment to production.

Responsibilities

• Fine-tune models (LoRA/QLoRA, RLHF, DPO, SFT) for tool-calling and domain tasks.
• Build data pipelines for cleaning, augmentation, and split data for training/validation.
• Conduct prompt engineering to optimize agent behavior in production.
• Design benchmarks: function-calling accuracy, retrieval precision, latency trade-offs.
• Develop end-to-end ML deployment for edge environments (IoT, embedded).
• Collaborate with AI Architect, Data Scientists, and Software Engineers.

Skills

LLM fine-tuning

Python

PyTorch

Hugging Face

LLM inference

GPU profiling

Benchmarking

Data pipelines

Deployment & infra

Communication

Education

Bachelor's degree in CS/Engineering/Data Science

Master's or PhD preferred

Tools

Docker

Kubernetes

Linux

NVIDIA Nemotron/NeMo

LangChain / LlamaIndex

MLflow / Weights & Biases

Job description

Quantiphi is seeking a senior Machine Learning Engineer to join the AI/ML team in Atlanta. You will own model fine-tuning, evaluation, and production deployment for AI agents and models used in industrial use cases. You will collaborate with AI Architects, Data Scientists, and deployment engineers to deliver end-to-end AI solutions.

You will optimize LLM/SLM agent behavior, build data pipelines, and develop benchmarking frameworks to balance accuracy and latency in real-time applications.