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Information Technology 🏢 Full Time ⭐️ Verified

Senior AI/ML Engineer

Nebula Dynamics
San Francisco
Estimated Salary
USD 180.000 – USD 250.000
New
Live Update
1 Juli 2026
Deadline
1 Jul 2027

Job Description

Welcome to Nebula Dynamics, where we are pioneering the next generation of intelligent systems. As a Senior AI/ML Engineer, you will be at the forefront of developing cutting-edge machine learning models that power our core products. We are looking for a visionary engineer who is passionate about Generative AI, Large Language Models (LLMs), and scalable data infrastructure.

In this role, you will drive the architectural decisions for our AI infrastructure, mentor junior engineers, and collaborate with product teams to translate complex business requirements into robust technical solutions.

Why Join Us?

  • Work on high-impact projects that shape the future of technology.
  • Competitive compensation and equity package.
  • Flexible remote-first policy with a focus on collaboration.
  • Access to the latest hardware and cloud resources for experimentation.

Responsibilities

  • Design, train, and deploy state-of-the-art machine learning models and deep learning architectures.
  • Build and maintain scalable MLOps pipelines for model training, validation, and productionization.
  • Optimize model performance for latency, throughput, and resource efficiency.
  • Collaborate with data scientists and software engineers to integrate AI models into production applications.
  • Conduct rigorous experimentation and A/B testing to drive product innovation.
  • Stay abreast of the latest research in the field of AI and implement best practices.

Qualifications

  • Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field.
  • 5+ years of professional experience in Machine Learning, Deep Learning, or AI engineering.
  • Strong proficiency in Python and major deep learning frameworks (PyTorch or TensorFlow).
  • Experience with LLMs, Transformers, and prompt engineering.
  • Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
  • Proven track record of shipping production-grade ML models.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning MLOps Docker Kubernetes AWS GCP Large Language Models Generative AI

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