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Science & Technology 🏢 Full Time ⭐️ Verified

Senior Machine Learning Engineer

Nexus AI Research Labs
San Francisco
Salary Estimate
USD 180.000 – USD 240.000
Live Update
17 Mei 2026
Deadline
17 Mei 2027

Job Description

Shape the Future of Artificial Intelligence

Nexus AI Research Labs is at the forefront of generative modeling and neural architecture search. We are seeking a visionary Senior Machine Learning Engineer to join our core research team in San Francisco. You will bridge the gap between cutting-edge academic research and scalable production-grade AI systems, working alongside world-class data scientists to solve complex algorithmic challenges.

If you are passionate about pushing the boundaries of what machine learning can achieve, we offer a collaborative, high-impact environment where your contributions will influence the next generation of AI-driven products.

Responsibilities

  • Architect and deploy large-scale machine learning models into production environments.
  • Collaborate with research scientists to implement and refine novel neural network architectures.
  • Optimize model training pipelines for throughput and efficiency using distributed computing frameworks.
  • Conduct deep-dive data analysis to identify performance bottlenecks and potential improvements.
  • Mentor junior engineers and promote best practices in code quality, documentation, and testing.
  • Stay abreast of the latest advancements in LLMs, computer vision, and reinforcement learning.
  • Contribute to the strategic technical roadmap for our proprietary AI infrastructure.

Qualifications

  • M.S. or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative discipline.
  • 5+ years of experience in developing and deploying machine learning systems at scale.
  • Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow.
  • Strong background in distributed systems and cloud infrastructure (AWS/GCP).
  • Proven track record of publishing research or shipping impactful ML features.
  • Deep understanding of model quantization, pruning, and distributed training techniques.
  • Ability to thrive in an agile, fast-paced research and development culture.

Required Skills

Machine Learning PyTorch TensorFlow Python Distributed Systems Cloud Architecture LLMs

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