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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI Engineer (Project 2026)

Nexus Future Systems
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
Live Update
28 Juni 2026
Deadline
28 Jun 2027

Job Description

We are on the cusp of a technological revolution. Nexus Future Systems is currently recruiting a visionary Senior AI Engineer to spearhead Project 2026—our flagship initiative to redefine artificial general intelligence infrastructure.

In this high-impact role, you will lead the architecture and deployment of next-generation neural networks. You will work alongside top-tier researchers and engineers to build scalable, secure, and efficient AI systems that will power the digital landscape of the future.

Why join us?

  • Work on cutting-edge technology that will define the industry for the next decade.
  • Competitive compensation package including equity options.
  • Flexible remote-first policy with access to state-of-the-art research labs.

If you are passionate about the future of AI and want to leave a legacy, we want to hear from you.

Responsibilities

  • Design and implement robust machine learning pipelines and large-scale neural network architectures for Project 2026.
  • Optimize existing models for speed, accuracy, and resource efficiency (latency/throughput).
  • Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate research into production-ready solutions.
  • Conduct rigorous research and experimentation to stay ahead of the curve in AI advancements.
  • Lead code reviews and mentor junior engineers to foster a culture of technical excellence.
  • Ensure compliance with data privacy regulations and ethical AI standards.

Qualifications

  • Master’s or PhD in Computer Science, Artificial Intelligence, or a related field (or equivalent practical experience).
  • Minimum of 5+ years of professional experience in AI/ML engineering, preferably in a high-scale production environment.
  • Expert proficiency in Python, PyTorch, or TensorFlow.
  • Strong understanding of Deep Learning architectures (Transformers, GANs, RNNs).
  • Experience with MLOps tools (Docker, Kubernetes, MLflow) and cloud platforms (AWS, GCP, or Azure).
  • Proven track record of leading technical projects and mentoring junior team members.

Required Skills

Python Machine Learning Deep Learning PyTorch TensorFlow NLP MLOps Docker Kubernetes AWS GCP Leadership System Architecture

Ready to Take This Challenge?

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