Position: AI/ML Engineer
Location: Wauwatosa WI***Day 1 Onsite***
Duration: 1 Years
| |
Role Overview Seeking an AI/ML Engineer to build optimize and deploy multimodal and LLM-based systems. The ideal candidate has strong experience in AI engineering computer vision cloud infrastructure and applied research.
Key Responsibilities
Develop end-to-end LLM/VLM pipelines for training fine-tuning and evaluation.
Architect multi-agent AI workflows using LangGraph Redis and Python.
Build scalable real-time inference services using FastAPI vLLM and AWS.
Implement computer vision solutions using OpenPose SAM2 and video classification models.
Create automated evaluation systems using LLM-as-a-Judge ROUGE-L and structured decoding.
Deploy and maintain reproducible AI infrastructure using Docker Kubernetes Helm Terraform.
Build observability dashboards and ensure performance across varied network conditions.
Conduct benchmarking of foundation models for multimodal and medical imaging tasks.
Contribute to research in NLP multimodal understanding and synthetic data generation.
Required Skills
Python PyTorch LLM/VLM training digital image processing
Cloud & infra: AWS Docker Kubernetes Helm Terraform
API & backend: FastAPI Flask
Strong foundations in NLP multimodal ML and evaluation methods
Preferred
Experience with medical imaging digital human/animation systems or healthcare AI
Publication record or research experience in NLP/vision
Keyword:
Skills: Digital : Machine LearningAI & Gen AI - Products & Tools
Experience Required: 6-8
|
Position: AI/ML Engineer Location: Wauwatosa WI***Day 1 Onsite*** Duration: 1 Years Role Overview Seeking an AI/ML Engineer to build optimize and deploy multimodal and LLM-based systems. The ideal candidate has strong experience in AI engineering computer vision cloud infrastructure and app...
Position: AI/ML Engineer
Location: Wauwatosa WI***Day 1 Onsite***
Duration: 1 Years
| |
Role Overview Seeking an AI/ML Engineer to build optimize and deploy multimodal and LLM-based systems. The ideal candidate has strong experience in AI engineering computer vision cloud infrastructure and applied research.
Key Responsibilities
Develop end-to-end LLM/VLM pipelines for training fine-tuning and evaluation.
Architect multi-agent AI workflows using LangGraph Redis and Python.
Build scalable real-time inference services using FastAPI vLLM and AWS.
Implement computer vision solutions using OpenPose SAM2 and video classification models.
Create automated evaluation systems using LLM-as-a-Judge ROUGE-L and structured decoding.
Deploy and maintain reproducible AI infrastructure using Docker Kubernetes Helm Terraform.
Build observability dashboards and ensure performance across varied network conditions.
Conduct benchmarking of foundation models for multimodal and medical imaging tasks.
Contribute to research in NLP multimodal understanding and synthetic data generation.
Required Skills
Python PyTorch LLM/VLM training digital image processing
Cloud & infra: AWS Docker Kubernetes Helm Terraform
API & backend: FastAPI Flask
Strong foundations in NLP multimodal ML and evaluation methods
Preferred
Experience with medical imaging digital human/animation systems or healthcare AI
Publication record or research experience in NLP/vision
Keyword:
Skills: Digital : Machine LearningAI & Gen AI - Products & Tools
Experience Required: 6-8
|
View more
View less
Job Location:
Monthly Salary:
Not Disclosed
Posted on:
18 hours ago
Vacancies:
1 Vacancy
