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Information Technology 🏒 Full Time ⭐️ Verified

Senior AI/ML Engineer - 2026 Vision

Nexus Horizon Labs
San Francisco
Estimated Salary
USD 180.000 – USD 280.000
Live Update
11 Mei 2026
Deadline
11 Mei 2027

Job Description

We are on the precipice of a technological revolution. Nexus Horizon Labs is seeking a visionary Senior AI/ML Engineer to architect the artificial intelligence systems that will define the year 2026 and beyond. We are building the infrastructure for next-generation Generative AI, Autonomous Systems, and Cognitive Computing.

In this pivotal role, you will lead the development of proprietary Large Language Models (LLMs) and reinforcement learning algorithms. You will work directly with our Chief Science Officer to solve unsolved problems in natural language processing and computer vision, ensuring our solutions are scalable, ethical, and transformative.

If you are passionate about the future of AI and want to shape the roadmap for the next decade, we want to hear from you.

Responsibilities

  • Architect and deploy state-of-the-art deep learning models with a focus on scalability and performance.
  • Lead research initiatives into Generative AI, fine-tuning LLMs for specialized enterprise applications.
  • Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate research into production-ready products.
  • Optimize existing ML pipelines for speed and efficiency, reducing latency in real-time inference environments.
  • Establish best practices for data governance, model monitoring, and ethical AI usage.
  • Mentor junior engineers and conduct code reviews to maintain high technical standards.
  • Qualifications

  • PhD or Master’s degree in Computer Science, Mathematics, Statistics, or a related technical field.
  • 5+ years of professional experience in Machine Learning, Deep Learning, or Natural Language Processing.
  • Expert proficiency in Python, PyTorch, and TensorFlow.
  • Strong understanding of distributed computing frameworks (e.g., Apache Spark, Kubernetes) and cloud platforms (AWS, GCP, or Azure).
  • Experience with MLOps tools such as MLflow, Kubeflow, or SageMaker.
  • Track record of publishing in top-tier conferences (NeurIPS, ICML, ACL) or open-sourcing significant projects.
  • Required Skills

    Python PyTorch TensorFlow Machine Learning Deep Learning NLP Large Language Models MLOps AWS Kubernetes Distributed Systems

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