Lead AI Engineer

Overview

Remote
Hybrid
Accepts corp to corp applications
Contract - 7 day((s))

Skills

LLM
MLLM
Nvidia AI
Pytorch
Tensorflow
VLM

Job Details

Hi ,
Greetings from Pro Integrate Consulting !
Hope you are doing well.

Job Title: Lead AI Engineer Video & Multimodal AI

Location: USA-Remote

Experience Level: 10+ Years

C2C

About the Role:
We are hiring a 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.

Best Regards,

Kranthi Y

Talent Acquisition Specialist, Pro Integrate Consulting

Email:

Contact: +1

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