Senior Machine Learning Engineer; Austin

Staff Machine Learning Engineer - LLMs / Mixture-of-Experts

(Hybrid Austin, US Citizens Only)

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, youll 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, youll feel right at home here.

This hybrid role is based in Austin, Texas , with relocation support available for qualified candidates. U.S. citizenship is required due to work involving security-sensitive projects .

• 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.

• 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 Tensor Flow.
• 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.

• 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).

Youll join a team that embodies transparency, ownership, tenacity, and humility - values that guide both technical decision-making and collaboration.

• 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

This role is hybrid in Austin with relocation assistance offered for the right candidate.

Only U.S. citizens are eligible due to the security clearance requirements.