Senior Principal, Machine Learning & Artificial Intelligence Job at Cherry Ventures (North Bethesda)

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

Atlassian is seeking a highly skilled and experienced Senior Principle Machine L...

Location

United States , Mountain View

Salary:

243100.00 - 407200.00 USD / Year

Atlassian

Expiration Date

Until further notice

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

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

What we offer

health coverage
paid volunteer days
wellness resources

Fulltime

Senior / Principal Machine Learning Scientist

Our mission is to restore cell health and resilience through cell rejuvenation t...

Location

United Kingdom , Cambridge

Salary:

136000.00 - 261050.00 GBP / Year

Altos Labs

Expiration Date

Until further notice

Requirements

Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field
6+ years of relevant post-PhD work experience in either an academic or industry setting
Proven experience developing and applying complex machine learning models
A strong track record of leading and publishing innovative, peer-reviewed research in top-tier ML conferences or high-impact scientific journals
Excellent scientific communication skills
Expertise in several of the following: deep learning, reinforcement learning, generative models, language models, computer vision, Bayesian inference, causal reasoning & inference, transfer & multi-task learning, graph neural networks, active learning, hybrid mechanistic/ML models
Proven experience applying sophisticated ML techniques to molecular and cell biological data sets

Job Responsibility

Pioneer novel machine learning methodologies and statistical frameworks
Contribute to setting the long-term technical vision and research strategy for a core domain within the Institute of Computation
Translate your deep understanding of the mathematical and theoretical underpinnings of cutting-edge AI research into high-impact applications
Design, implement, and optimize large-scale machine learning systems using modern frameworks and agile practices
Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters
Develop robust approaches for multi-modal data integration and cross-domain mapping to extract actionable biological insights
Apply computational thinking to solve problems in drug target identification, compound assessment, and prediction of cellular perturbation responses
Lead the full ML development lifecycle from theoretical conception and data strategy through model development, training, and evaluation
Act as a key technical mentor to Machine Learning Scientists and Engineers

Fulltime

Senior / Principal Machine Learning Scientist

Our mission is to restore cell health and resilience through cell rejuvenation t...

Location

United States , Redwood City; San Diego

Salary:

260950.00 - 509450.00 USD / Year

Altos Labs

Expiration Date

Until further notice

Requirements

Ph.D. in Machine Learning, Computer Science, Artificial Intelligence, Statistics, or a related quantitative field
6+ years of relevant post-PhD work experience in either an academic or industry setting
Proven experience developing and applying complex machine learning models
A strong track record of leading and publishing innovative, peer-reviewed research in top-tier ML conferences or high-impact scientific journals
Excellent scientific communication skills
Expertise in several of the following: deep learning, reinforcement learning, generative models, language models, computer vision, Bayesian inference, causal reasoning & inference, transfer & multi-task learning, graph neural networks, active learning, hybrid mechanistic/ML models
Proven experience applying sophisticated ML techniques to molecular and cell biological data sets

Job Responsibility

Pioneer novel machine learning methodologies and statistical frameworks
Contribute to setting the long-term technical vision and research strategy for a core domain
Translate your deep understanding of the mathematical and theoretical underpinnings of cutting-edge AI research into high-impact applications
Design, implement, and optimize large-scale machine learning systems
Develop and manage efficient distributed training strategies across multiple GPUs and compute clusters
Develop robust approaches for multi-modal data integration and cross-domain mapping
Apply computational thinking to solve problems in drug target identification, compound assessment, and prediction of cellular perturbation responses
Lead the full ML development lifecycle
Act as a key technical mentor to Machine Learning Scientists and Engineers

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