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Staff Machine Learning Engineer

weareorbis.com Logo

Orbis Consultants

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Location:
United States, Austin

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Category:
IT - Software Development

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Contract Type:
Not provided

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Salary:

Not provided

Job Description:

Are you excited by the challenge of pushing the boundaries of what modern AI models can do – especially when data is limited? A fast-growing AI platform is looking for a Staff Machine Learning Engineer to help shape the next generation of large-scale intelligent systems. In this role, you’ll take the lead on developing advanced Large Language Models (LLMs) and Mixture-of-Experts (MoE) architectures, driving innovation that directly influences product capabilities and performance. If you thrive at the intersection of research and real-world impact, you’ll feel right at home here.

Job Responsibility:

  • Architect, train, and optimize cutting-edge LLMs and MoE-based systems
  • Experiment with novel algorithms to improve efficiency, scalability, and model performance
  • Collaborate closely with engineering and product teams to deploy ML capabilities into production
  • Contribute to pioneering research in ML and NLP, driving methodological advancements
  • Mentor engineers and help shape technical best practices across the organisation

Requirements:

  • Advanced degree in Computer Science or a related field (PhD preferred)
  • 6+ years of industry experience building and deploying machine learning models at scale
  • Deep expertise in LLMs, Mixture-of-Experts architectures, and modern ML frameworks such as PyTorch or TensorFlow
  • Demonstrated innovation through impactful research, patents, or production-grade ML systems
  • Ability to lead complex, cross-functional technical initiatives
  • Strong problem-solving skills and a passion for pushing the boundaries of AI

Nice to have:

  • Publications or conference presentations at leading ML/NLP venues such as NeurIPS, ICML, ICLR, AAAI, EMNLP, NACL, ACL, EACL, CoNLL, or similar
  • Experience with cloud platforms (AWS, Azure, GCP) and distributed computing tools (Spark, Hadoop)
  • Familiarity with containerization and orchestration (Docker, Kubernetes)
What we offer:
  • Competitive compensation and performance incentives
  • Comprehensive medical, dental, and vision benefits
  • Monthly wellness stipend + annual continuing education credit
  • A flexible work environment and unlimited approved PTO
  • Parental and bereavement leave and other employee support programs
  • Relocation support available

Additional Information:

Job Posted:
December 11, 2025

Employment Type:
Fulltime
Work Type:
Hybrid work
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