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Senior AI Engineer - Project 2026

OmniFuture Corp
San Francisco
Estimated Salary
USD 185.000 – USD 260.000
Live Update
15 Mei 2026
Deadline
15 Mei 2027

Job Description

Are you ready to architect the future of intelligent systems? OmniFuture Corp is seeking a visionary Senior AI Engineer to join our elite team working on Project 2026. In this pivotal role, you will define the roadmap for next-generation generative AI, optimizing models for speed, scalability, and ethical deployment. Join us in building the technologies that will define the decade ahead.

About Project 2026

Project 2026 is our most ambitious initiative yet, aimed at revolutionizing how humans interact with machine intelligence. We are moving beyond standard automation to create adaptive, self-learning systems capable of solving complex global challenges.

Why Join Us?

  • Work on cutting-edge AI research with a competitive salary and equity package.
  • Flexible remote-first culture with access to state-of-the-art infrastructure.
  • Opportunity to mentor junior engineers and shape the future of the industry.

Responsibilities

  • Design, train, and deploy scalable machine learning models using Python and deep learning frameworks.
  • Lead the optimization of inference pipelines to reduce latency and resource consumption by 40%.
  • Collaborate with cross-functional teams (Product, Research, Security) to integrate AI solutions into real-world applications.
  • Stay ahead of the curve on emerging technologies, specifically focusing on Agentic AI and Neural Architecture Search for the 2026 roadmap.
  • Conduct rigorous code reviews and establish best practices for MLOps and model governance.

Qualifications

  • B.S., M.S., or Ph.D. in Computer Science, Mathematics, or a related field.
  • 5+ years of professional experience in AI/ML engineering, with at least 2 years leading complex model deployments.
  • Expert proficiency in Python, TensorFlow, and PyTorch.
  • Strong understanding of distributed computing systems (e.g., Kubernetes, AWS SageMaker) and GPU acceleration (CUDA).
  • Experience with large language models (LLMs) and Natural Language Processing (NLP) techniques.

Responsibilities

  • Design, train, and deploy scalable machine learning models using Python and deep learning frameworks.
  • Lead the optimization of inference pipelines to reduce latency and resource consumption by 40%.
  • Collaborate with cross-functional teams (Product, Research, Security) to integrate AI solutions into real-world applications.
  • Stay ahead of the curve on emerging technologies, specifically focusing on Agentic AI and Neural Architecture Search for the 2026 roadmap.
  • Conduct rigorous code reviews and establish best practices for MLOps and model governance.
  • Qualifications

  • B.S., M.S., or Ph.D. in Computer Science, Mathematics, or a related field.
  • 5+ years of professional experience in AI/ML engineering, with at least 2 years leading complex model deployments.
  • Expert proficiency in Python, TensorFlow, and PyTorch.
  • Strong understanding of distributed computing systems (e.g., Kubernetes, AWS SageMaker) and GPU acceleration (CUDA).
  • Experience with large language models (LLMs) and Natural Language Processing (NLP) techniques.
  • Required Skills

    Python TensorFlow PyTorch NLP Deep Learning Machine Learning MLOps Kubernetes AWS CUDA AI Architecture

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