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Information Technology 🏒 Full Time ⭐️ Verified

Senior AI/ML Engineer

Nebula Tech Solutions
San Francisco
Estimated Salary
USD 180.000 – USD 260.000
New
Live Update
16 Mei 2026
Deadline
16 Mei 2027

Job Description

Are you ready to engineer the future of intelligence?

Nebula Tech Solutions is seeking a visionary Senior AI/ML Engineer to join our elite R&D team in San Francisco. In this pivotal role, you will architect and deploy state-of-the-art machine learning systems that redefine industry standards. We are looking for a problem solver who thrives in a high-growth environment and is passionate about the intersection of deep learning and scalable infrastructure.

As a key member of our team, you will bridge the gap between theoretical research and production-grade code, ensuring our AI models are robust, efficient, and ready for the demands of 2024 and beyond.

Responsibilities

  • Design, train, and deploy advanced machine learning and deep learning models for large-scale production environments.
  • Collaborate with data scientists and software engineers to optimize data pipelines and model inference.
  • Implement best practices for MLOps, including version control, CI/CD, and model monitoring.
  • Conduct rigorous code reviews and mentor junior engineers to foster a culture of technical excellence.
  • Research and evaluate new technologies to keep our stack at the forefront of AI innovation.

Qualifications

  • Master’s degree or PhD in Computer Science, Mathematics, or a related technical field.
  • 5+ years of professional experience in AI/ML engineering, with a focus on Python and deep learning frameworks (PyTorch, TensorFlow, or JAX).
  • Strong proficiency in cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
  • Proven track record of shipping production-ready machine learning models.
  • Excellent communication skills and the ability to translate complex technical concepts for diverse stakeholders.

Required Skills

Python PyTorch TensorFlow Machine Learning Deep Learning AWS Docker Kubernetes MLOps SQL

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