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

Atlassian

Location:
United States, Mountain View

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

243100.00 - 407200.00 USD / Year

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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

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