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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

Shape the Future of Generative AI

At Nexus AI Labs, we are pushing the boundaries of what is possible with large-scale deep learning models. We are looking for an experienced Senior Machine Learning Engineer to join our core research and infrastructure team. You will be instrumental in designing, training, and deploying high-performance models that power our next-generation enterprise solutions.

You will work in a fast-paced environment where innovation is the standard, collaborating with world-class researchers and engineers to solve complex architectural challenges.

Responsibilities

  • Architect and implement scalable ML training pipelines using PyTorch or TensorFlow.
  • Optimize neural network architectures for latency and throughput in production environments.
  • Collaborate with research scientists to prototype and productionize state-of-the-art NLP models.
  • Design distributed training strategies for models with billions of parameters.
  • Mentor junior engineers and promote rigorous code quality and engineering best practices.
  • Monitor and analyze model performance, implementing automated retraining loops.
  • Stay current with evolving academic research to maintain the company's competitive edge.

Qualifications

  • Master's or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
  • 5+ years of experience in production-level machine learning engineering.
  • Deep expertise in Python and C++ for high-performance computing.
  • Hands-on experience with cloud infrastructure (AWS/GCP) and containerization (Docker/Kubernetes).
  • Strong understanding of Transformer architectures and attention mechanisms.
  • Proven track record of deploying ML models to large-scale production environments.
  • Excellent communication skills with the ability to bridge the gap between research and production.

Required Skills

Python PyTorch TensorFlow Deep Learning NLP Distributed Systems Kubernetes AWS MLOps

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