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Senior Principal Machine Learning Engineer - LLM Post-Training and Optimization

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Atlassian

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Location:
United States , Mountain View

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Contract Type:
Not provided

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Salary:

243100.00 - 407200.00 USD / Year

Job Description:

Atlassian is seeking a highly skilled and experienced Senior Principle Machine Learning Engineer to propel our efforts in Large Language Model (LLM) post-training and optimization, shaping the future of intelligent, team-centric solutions.

Job Responsibility:

  • Lead the fine-tuning and post-training optimization of large language models (LLMs) for diverse applications
  • Develop and implement techniques for model compression, quantization, pruning, and knowledge distillation to optimize performance and reduce computational costs
  • Conduct research on advanced techniques in transfer learning, reinforcement learning, and prompt engineering for LLMs
  • Design and execute rigorous benchmarking and evaluation frameworks to assess model performance across multiple dimensions
  • Collaborate with infrastructure teams to optimize LLM deployment pipelines, ensuring scalability and efficiency in production environments
  • Stay at the forefront of advancements in LLM technologies, sharing insights, driving innovation within the team, and leading agile development
  • Mentoring other team members, facilitating within/across team workshops, fostering a culture of technical excellence and continuous learning

Requirements:

  • Ph.D. or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field
  • 8+ years of experience in machine learning, with a focus on large-scale model development and optimization
  • Deep expertise in LLM and transformer architectures (e.g., GPT, BERT, T5)
  • Strong proficiency in Python and ML frameworks such as PyTorch, JAX, or TensorFlow
  • Experience with distributed training techniques and large-scale data processing pipelines
  • Proven track record of deploying machine learning models in production environments
  • Familiarity with model optimization techniques, including quantization, pruning, and knowledge distillation
  • Strong problem-solving skills and ability to work in a fast-paced, collaborative environment
  • Excellent communication skills and ability to translate technical concepts for diverse audiences

Nice to have:

  • Experience with multi-modal LLMs or domain-specific fine-tuning
  • Knowledge of cloud-based ML platforms (e.g., AWS, GCP, Azure)
  • Contributions to open-source ML projects or publications in top-tier conferences
  • Familiarity with MLOps practices and tools
What we offer:
  • health coverage
  • paid volunteer days
  • wellness resources

Additional Information:

Job Posted:
April 23, 2025

Employment Type:
Fulltime
Work Type:
Remote work
Job Link Share:

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