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Information Technology 🏢 Full Time ⭐️ Verified

Senior Machine Learning Engineer

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

Job Description

Are you ready to redefine the boundaries of artificial intelligence? Nexus AI Labs is seeking a visionary Senior Machine Learning Engineer to join our core research and development team in San Francisco. We build cutting-edge generative models that solve complex real-world problems at scale. In this role, you will lead high-impact projects, mentor junior engineers, and collaborate with world-class researchers to deploy performant production models.

We offer a dynamic, fast-paced environment where innovation is the standard, not the exception. Join us as we push the limits of what's possible in the Science & Technology sector.

Responsibilities

  • Architect and implement scalable machine learning pipelines for training large-scale models.
  • Design and refine novel algorithms to improve model accuracy and inference latency.
  • Collaborate with product and data engineering teams to integrate ML solutions into production environments.
  • Conduct rigorous performance analysis and model evaluation to ensure system reliability.
  • Provide technical leadership and mentorship to the engineering team.
  • Contribute to the research roadmap by investigating emerging trends in neural architectures.
  • Optimize resource utilization across distributed GPU computing clusters.

Qualifications

  • Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related quantitative field.
  • 5+ years of professional experience in deep learning, NLP, or computer vision.
  • Expertise in Python and deep learning frameworks such as PyTorch or TensorFlow.
  • Deep understanding of cloud infrastructure (AWS/GCP) and containerization (Docker/Kubernetes).
  • Strong knowledge of distributed computing and optimization techniques.
  • Excellent communication skills with the ability to explain complex technical concepts to cross-functional stakeholders.
  • Track record of published research or successful production-grade ML implementations.

Required Skills

Machine Learning Deep Learning Python PyTorch Kubernetes MLOps Distributed Systems Neural Networks

Ready to Take on This Challenge?

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