Senior Artificial Intelligence Engineer

Location: Onsite in Memphis, Tennessee, United States

Salary: $86,320–$154,960 per year

Company

hirify.global is a biomedical research and healthcare institution with high-performance research computing and bioimage informatics programs.

What you will do

• Build, evaluate, fine-tune, deploy, and benchmark large language models, agentic AI systems, and multimodal foundation models.
• Design shared AI architecture, secure environments, reference architectures, standards, and operating procedures.
• Develop AI-enabled services, proof-of-concepts, pilots, demonstrations, workshops, and training materials.
• Optimize GPU and HPC resource allocation, distributed training, inference performance, cost, and utilization.
• Implement safety guardrails, sandboxing, access controls, audit logging, and privacy protections for sensitive research data.
• Collaborate with scientists, analysts, business stakeholders, information services professionals, vendors, and software engineers.

Requirements

• Master’s degree in computer science, computer engineering, data science, information technology, or a related field.
• At least four years of experience designing and developing large-scale AI/ML systems or AI/ML product features.
• Strong experience with supervised and unsupervised machine learning and deep learning industry use cases.
• Experience with TensorFlow, Keras, PyTorch, time-series analysis, anomaly detection, forecasting, predictive modeling, graph-based neural networks, Bayesian statistics, and text analytics.
• Technical leadership experience, including setting standards, mentoring, and cross-team collaboration.
• Must work onsite in Memphis, Tennessee.

Nice to have

• PhD in data science, computer science, computer engineering, information technology, or a related field.
• Hands-on experience with LLM or multimodal model adaptation, PEFT/LoRA, instruction tuning, and preference optimization.
• Experience with multi-GPU training, CUDA, NCCL, Slurm, vLLM, TensorRT-LLM, Triton, quantization, batching, and speculative decoding.
• Experience with AI security, reproducible benchmarking, observability, versioning, rollback, cost control, and incident response.
• Biomedical research, imaging, regulated health data, or open-source AI/ML infrastructure experience.

Culture & Benefits

• Collaborative work across high-performance research computing, bioimage informatics, science, and information services.
• Hands-on ownership of AI systems from prototype through production operation.
• Opportunity to develop workshops and training classes for AI adoption.
• Benefits are provided as part of the hospital’s employment package.