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Senior​/Principal Visual ML Engineer

Remote / Online - Candidates ideally in
Charleston, Charleston County, South Carolina, 29408, USA
Listing for: TriNet Group
Remote/Work from Home position
Listed on 2026-10-03
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 180000 - 240000 USD Yearly USD 180000.00 240000.00 YEAR
Job Description & How to Apply Below

Travel Requirement: 0-10%, Quarterly for meetings

Office

Location:

Remote, US Based

JOB SUMMARY:

We are seeking a Senior/Principal Machine Learning Engineer with deep expertise in Visual Language Models (VLMs), Large Vision Models (LVMs), Generative AI, and multimodal foundation models to build the next generation of AI-powered creative technologies.

This is a hands-on technical role responsible for architecting, developing, and deploying state-of-the-art AI systems for image, video, and creative generation. You will work closely with Product, Engineering, Data Science, and Design teams to build production-scale GenAI capabilities that power creative automation, digital advertising, content personalization, and campaign optimization.

You will drive innovation across the entire lifecycle, from research and experimentation through large-scale production deployment, while helping establish the company's long-term Visual AI strategy.

ESSENTIAL FUNCTIONS AND RESPONSIBILITIES:
Visual AI & Generative AI Development
  • Design and develop production-grade AI systems for:
    • Image generation
    • Video generation
    • Image editing and enhancement
    • Creative optimization
    • Style transfer
    • Multimodal content understanding
    • Brand-aware content generation
    • AI-assisted creative workflows
  • Build scalable pipelines for automated creative generation across multiple marketing channels.
  • Research and implement state-of-the-art diffusion, transformer, autoregressive, and multimodal architectures.
  • Fine-tune and optimize foundation models for enterprise production use cases
Develop and optimize systems using:
  • Transformer-based image/video generation
  • Visual reasoning models
  • Train, fine-tune, optimize, and deploy large-scale generative AI models using advanced techniques including LoRA, QLoRA, PEFT, distillation, quantization, and prompt optimization.
  • Build robust model evaluation frameworks to measure creative quality, visual fidelity, consistency, brand alignment, safety, hallucination risk, and human preference alignment.
  • Improve model performance across quality, latency, scalability, and cost through continuous experimentation, benchmarking, and production optimization
Lead development and building of AI systems for:
  • Motion transfer
  • Storyboarding
  • Dynamic creative optimization
System Architecture & Technical Requirements
  • Lead decisions around foundation models, fine-tuning strategies, RAG pipelines, embeddings, and ranking systems.
  • Deep expertise in Generative AI, multimodal foundation models, Vision Language Models (VLMs), Large Vision Models (LVMs), diffusion models, transformers, and autoregressive architectures, with hands-on experience building image and video generation systems using leading models such as FLUX, Stable Diffusion, Imagen, Veo, Runway, Kling, and open-source video diffusion models.
  • Strong experience with computer vision and multimodal AI frameworks (CLIP, Florence, Qwen-VL, LLaVA, SAM, YOLO, Grounding DINO) and applying them to visual understanding, generation, editing, and creative optimization.
  • Proven ability to product ionize large-scale AI models using modern ML infrastructure including Hugging Face, Diffusers, Deep Speed, FSDP, TensorRT, ONNX, CUDA/GPU optimization, and cloud-native MLOps platforms (AWS/GCP/Azure, Kubernetes, Kubeflow, MLflow, distributed inference).
  • Architect and oversee scalable LLM/GenAI systems for Mar Tech/AdTech use cases
  • Design and deploy multi-agent systems using frameworks such as Lang Graph, Auto Gen, CrewAI, MCP, or equivalent.
  • Own end-to-end ML system design: data ingestion, feature pipelines, training, inference, evaluation, and monitoring.
Cross-Functional Collaboration
  • Work closely with Product, Data, and Platform teams to translate business needs into scalable ML capabilities.
  • Communicate complex ML concepts…
Position Requirements
10+ Years work experience
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