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Information Technology 🏒 Full Time ⭐️ Verified

Senior AI/ML Engineer (2026 Vision)

Nexus Dynamics
San Francisco
Estimated Salary
USD 180.000 – USD 240.000
Live Update
12 Mei 2026
Deadline
12 Mei 2027

Job Description

Join the Architects of Tomorrow. Nexus Dynamics is on a mission to revolutionize the technology landscape by 2026. We are seeking a highly skilled Senior AI/ML Engineer to lead our advanced research division. In this pivotal role, you will not just build models; you will define the architectural standards for the next generation of artificial intelligence, focusing on scalability, ethical AI, and real-time generative capabilities.

As a key member of our R&D team, you will bridge the gap between theoretical breakthroughs and production-grade applications. We offer a competitive package and a culture that prioritizes innovation and autonomy.

Responsibilities

  • Architect and deploy scalable machine learning pipelines capable of handling petabyte-scale data sets.
  • Lead the research and development of cutting-edge Large Language Models (LLMs) and generative AI frameworks.
  • Optimize model inference for low-latency environments in high-traffic production systems.
  • Establish best practices for MLOps, ensuring continuous integration and deployment of AI models.
  • Collaborate with cross-functional teams to translate business requirements into technical AI solutions.
  • Conduct rigorous code reviews and mentor junior engineers to foster a culture of technical excellence.
  • Publish research findings and contribute to open-source communities to drive industry standards.

Qualifications

  • Master’s or PhD in Computer Science, Artificial Intelligence, or a related field.
  • Minimum of 5 years of professional experience in building and deploying production ML models.
  • Deep proficiency in Python, PyTorch, TensorFlow, or JAX.
  • Strong understanding of distributed systems, cloud infrastructure (AWS/GCP/Azure), and containerization (Docker/Kubernetes).
  • Experience with vector databases and RAG (Retrieval-Augmented Generation) architectures.
  • Proven track record of improving model accuracy and reducing inference costs.
  • Excellent communication skills and the ability to articulate complex technical concepts to non-technical stakeholders.

Required Skills

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

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