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Senior Machine Learning Engineer - Generative AI

Nexus AI Labs
San Francisco
Salary Estimate
USD 180.000 – USD 250.000
Latest
Live Update
22 Mei 2026
Deadline
22 Mei 2027

Job Description

At Nexus AI Labs, we are at the forefront of revolutionizing human-computer interaction through advanced Generative AI. We are seeking a visionary Senior Machine Learning Engineer to join our elite R&D team in San Francisco. You will be responsible for architecting and deploying large-scale machine learning systems that power our next generation of intelligent applications.

If you are passionate about pushing the boundaries of LLMs, fine-tuning foundation models, and solving complex scalability challenges, we want to hear from you.

Responsibilities

  • Model Development: Design, train, and fine-tune state-of-the-art deep learning models, specifically focusing on Large Language Models (LLMs) and Computer Vision.
  • Infrastructure Optimization: Build and maintain high-performance training and inference pipelines using distributed computing frameworks (e.g., Ray, Kubernetes).
  • Research Integration: Stay abreast of the latest academic research and integrate novel techniques into production systems.
  • Code Review & Mentorship: Lead technical reviews, contribute to the engineering codebase, and mentor junior engineers and data scientists.
  • Deployment: Oversee the end-to-end deployment of models to cloud environments, ensuring high availability and monitoring.

Qualifications

  • Education: MS or PhD in Computer Science, Mathematics, or a related field, with a focus on AI/ML.
  • Experience: 5+ years of professional experience in Machine Learning engineering or Applied Research.
  • Programming: Expert proficiency in Python, C++, and deep learning frameworks (PyTorch or TensorFlow).
  • Domain Knowledge: Proven track record working with NLP, Transformers, or Generative Adversarial Networks (GANs).
  • Tools: Strong experience with MLOps tools (Docker, MLflow) and cloud platforms (AWS, GCP, or Azure).

Required Skills

Python PyTorch TensorFlow NLP LLMs Deep Learning MLOps Kubernetes AWS Docker Machine Learning Natural Language Processing

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