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Information Technology 🏒 Full Time ⭐️ Verified

Senior Artificial Intelligence Engineer

Nexus Future Technologies
San Francisco
Estimated Salary
USD 180.000 – USD 240.000
Live Update
11 Mei 2026
Deadline
11 Mei 2027

Job Description

We are building the future of intelligence. Nexus Future Technologies is seeking a visionary Senior AI Engineer to lead the development of next-generation Large Language Models (LLMs) and autonomous systems. In this pivotal role, you will define the technical roadmap for our AI infrastructure, pushing the boundaries of what is possible in 2026 and beyond. If you are passionate about scalable machine learning, generative AI, and building systems that think, we want to hear from you.

We offer a competitive compensation package, equity options, and the opportunity to work with world-class engineers in a cutting-edge environment.

Responsibilities

  • Architect and deploy state-of-the-art machine learning models and neural networks at scale.
  • Lead the end-to-end lifecycle of AI development, from data ingestion and preprocessing to model training, evaluation, and productionization.
  • Optimize existing models for inference speed, accuracy, and resource efficiency using techniques such as quantization and distillation.
  • Collaborate with cross-functional teams (Product, Engineering, and Design) to translate business requirements into robust technical solutions.
  • Mentor junior data scientists and engineers, fostering a culture of innovation and continuous learning.
  • Stay abreast of the latest advancements in AI research and integrate cutting-edge techniques into our production stack.

Qualifications

  • Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
  • Minimum of 5+ years of professional experience in Machine Learning, Deep Learning, or AI engineering.
  • Strong proficiency in Python, PyTorch, or TensorFlow.
  • Extensive experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
  • Proven track record of deploying large-scale ML systems in production environments.
  • Excellent problem-solving skills and the ability to thrive in a fast-paced, agile environment.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning LLMs NLP AWS GCP Docker Kubernetes SQL Data Pipelines

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