Lead AI Engineer – Video & Multimodal AI

Brillfy Technology Inc; United States; Remote; USD 170,000 - 720,000; Full time

Job summary

A leading company in AI technology is seeking a Lead AI Engineer specializing in video and multimodal AI. The role involves designing and deploying advanced AI systems, optimizing models, and collaborating with cross-functional teams. Candidates should have extensive experience in AI/ML, particularly in deep learning and video intelligence, and a strong academic background. This is a full-time remote position offering competitive compensation.

Qualifications

• 10+ years of industry or research experience in AI/ML.
• Advanced proficiency in Python and DL frameworks.

Responsibilities

• Architect and lead the development of large-scale video AI models.
• Collaborate with data scientists and researchers on model development.

Skills

Python

Deep Learning

MLOps

Education

MS or Postgraduate degree in Computer Science

PhD preferred

Tools

PyTorch

TensorFlow

Docker

Kubernetes

MLFlow

Job description

Lead AI Engineer – Video & Multimodal AI

Lead AI Engineer – Video & Multimodal AI

Direct message the job poster from Brillfy Technology Inc

Clients Partner at Brillfy Technology Inc.

Position: Lead AI Engineer – Video & Multimodal AI

Location: Remote

Duration: Full Time

Experience Level: 10+ Years Experience

Job Description:

About the Role:

We are hiring a Lead AI Engineer to spearhead the design, fine-tuning, and scalable deployment of cutting-edge AI systems, with a focus on deep learning, video intelligence, and multi-modal (vision + language) models. The ideal candidate has a strong academic foundation, preferably from Ivy League institutions—and proven experience in driving innovative AI solutions from research to production.

Key Responsibilities:

• Architect and lead the development of large-scale video AI and vision-language models (VLMs).
• Fine-tune and optimize Large Language Models (LLMs) and Multi-modal Large Language Models (MLLMs) for task-specific applications.
• Scale model training and evaluation across distributed systems with an emphasis on GPU/accelerated environments.
• Build and maintain robust AI pipelines for training, evaluation, benchmarking, and deployment using state-of-the-art MLOps tools.
• Drive performance optimization of models for real-time inference using tools like TensorRT, ONNX, and NVIDIA Triton.
• Collaborate cross-functionally with data scientists, researchers, and platform engineers to align model development with business goals.
• Publish internal/external papers and contribute to IP creation and thought leadership in AI innovation.

Minimum Qualifications:

• MS or Postgraduate degree in Computer Science or related field (PhD preferred); strong preference for Ivy League graduates.
• 10+ years of industry or research experience in AI/ML, with a focus on Deep Learning, Video AI, and multi-modal systems.
• Advanced proficiency in Python and DL frameworks such as PyTorch and TensorFlow.
• Deep expertise in fine-tuning LLMs and MLLMs, including prompt engineering, transfer learning, and embedding-based techniques.
• Proven experience scaling AI model training and inference across multi-GPU and distributed compute platforms.
• Strong hands-on knowledge of MLOps practices, including Docker, Kubernetes, MLFlow, and model serving.

Preferred Skills:

• Familiarity with NVIDIA’s AI ecosystem (TensorRT, Triton Inference Server, DeepStream SDK).
• Experience with retrieval-augmented generation (RAG), attention-based models, and real-time video inference.
• Prior experience in leading AI teams or projects and mentoring junior researchers/engineers.
• Publications, patents, or open-source contributions in the field of AI/ML.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Information Technology

• Industries

  IT Services and IT Consulting

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