Senior/Principal Visual ML Engineer

Travel Requirement: 0-10%, Quarterly for meetings, 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

Vision & Multimodal ML

Develop and optimize systems using:

• Vision Language Models (VLMs)
• Large Vision Models (LVMs)
• Multimodal LLMs
• Diffusion models
• Transformer-based image/video generation
• Contrastive vision-language models
• Image-text alignment models
• Visual reasoning models

Model Development & Optimization

• 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:

• Text-to-video generation
• Image-to-video generation
• Video editing
• AI avatars
• Motion transfer
• Storyboarding
• Creative sequencing
• Marketing video generation
• 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 productionize large-scale AI models using modern ML infrastructure including Hugging Face, Diffusers, DeepSpeed, 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 MarTech/AdTech use cases
• Design and deploy multi-agent systems using frameworks such as LangGraph, AutoGen, 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 clearly to executive leadership, stakeholders, and the Board.
• Contribute to technical narratives used for fundraising, company valuation, and strategic planning.

• MS or PhD in Computer Science, Artificial Intelligence, Machine Learning, Computer Vision, Robotics, or a related field.
• 8-12+ years of experience developing production ML systems.
• 5+ years of experience in Deep Learning and Computer Vision.
• 3+ years of hands-on experience with Generative AI for images and video.
• Expert-level proficiency in Python and PyTorch.
• Strong software engineering fundamentals with production-quality code.
• Solid understanding of distributed systems, GPU optimization, batching, and cost-aware inference.
• Excellent software engineering fundamentals (Python, APIs, microservices, Docker, Kubernetes).

PHYSICAL REQUIREMENTS/WORKING CONDITIONS:

Standing/Walking/Mobility: Must have mobility to attend meetings remotely and in person.

Climbing/Stooping/Kneeling: 0% - 10% of the time.

Lifting/Pulling/Pushing: 0% - 10% of the time.

Fingering/Grasping/Feeling: Must be able to write, type and use a telephone system 100% of the time.