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Information Technology 🏒 Full Time ⭐️ Verified

Senior AI Engineer - Project 2026

Nebula AI Systems
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
New
Live Update
3 Juli 2026
Deadline
3 Jul 2027

Job Description

The Future of Intelligence Starts Here.

We are looking for a visionary Senior AI Engineer to join our elite Project 2026 initiative. As a leader in next-generation generative AI, Nebula AI Systems is redefining the boundaries of machine learning, focusing on creating autonomous, self-improving models for the enterprise sector. You will be at the forefront of developing the algorithms that will power the digital world of tomorrow.

In this role, you won't just implement existing solutions; you will architect the infrastructure for scalable, multimodal AI systems. We offer a competitive compensation package, equity opportunities, and a collaborative environment that challenges the status quo.

Responsibilities

  • Architect and deploy large-scale generative AI models and LLMs focused on reasoning and autonomy.
  • Optimize model inference latency and reduce costs in cloud environments using advanced quantization and pruning techniques.
  • Collaborate with cross-functional teams of researchers and engineers to translate theoretical AI breakthroughs into production-ready software.
  • Design robust MLOps pipelines ensuring high availability and monitoring for AI workloads.
  • Experiment with cutting-edge architectures including Transformers, Diffusion models, and Reinforcement Learning from Human Feedback (RLHF).
  • Lead code reviews and mentor junior engineers to foster a culture of technical excellence.

Qualifications

  • 5+ years of professional experience in software engineering, with at least 3 years specializing in Machine Learning or AI.
  • Deep expertise in Python, PyTorch, or TensorFlow.
  • Experience with distributed computing frameworks (Apache Spark, Ray) and cloud platforms (AWS, GCP, or Azure).
  • Strong understanding of statistical learning, NLP, and deep learning fundamentals.
  • Experience deploying models to production environments using Docker and Kubernetes.
  • Excellent problem-solving skills and the ability to thrive in a fast-paced, agile environment.
  • Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field is a plus.

Required Skills

Python PyTorch TensorFlow MLOps AWS Kubernetes Docker NLP LLM Generative AI Machine Learning Distributed Systems

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