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Senior AI Engineer - Generative Models

Aether Dynamics
San Francisco
Estimated Salary
USD 160.000 – USD 240.000
New
Live Update
30 Juni 2026
Deadline
30 Jun 2027

Job Description

The Opportunity:

Aether Dynamics is at the forefront of the artificial intelligence revolution. We are seeking a visionary Senior AI Engineer to lead the development and deployment of next-generation Generative AI models. You will work directly with our research team to bridge the gap between theoretical models and scalable production systems.

Why Join Aether Dynamics?

  • Work with state-of-the-art hardware and large language models (LLMs).
  • Competitive compensation package including equity.
  • Flexible remote-first work environment.

Core Responsibilities:

  • Architect and implement robust machine learning pipelines for LLM fine-tuning and deployment.
  • Conduct cutting-edge research in Natural Language Processing (NLP) and multimodal learning.
  • Optimize model inference latency and throughput for real-time applications.
  • Mentor junior engineers and conduct code reviews to maintain high engineering standards.
  • Collaborate with cross-functional product teams to define AI-driven features.

Qualifications:

  • Ph.D. or Master’s degree in Computer Science, Statistics, or a related field.
  • 5+ years of professional experience in AI/ML engineering.
  • Expert proficiency in Python, PyTorch, and TensorFlow.
  • Deep understanding of Transformer architectures and attention mechanisms.
  • Experience with MLOps tools (Kubernetes, MLflow, AWS SageMaker).

Responsibilities

  • Design and implement scalable machine learning infrastructure.
  • Pioneering research in Natural Language Processing (NLP) and multimodal AI.
  • Optimize model inference latency and throughput.
  • Mentor junior engineers and contribute to technical architecture decisions.
  • Ensure data quality and integrity across training datasets.
  • Qualifications

  • Ph.D. or M.S. in Computer Science, Statistics, or related field.
  • 5+ years of experience in AI/ML engineering.
  • Proficiency in Python, PyTorch, and TensorFlow.
  • Deep understanding of neural network architectures.
  • Experience with distributed training frameworks.
  • Required Skills

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

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