Staff Machine Learning Engineer
$230k - 280k per year
Permanent
Remote
US
  • Staff Applied Machine Learning Engineer
  • Remote (must be based in USA)
  • Work Authorization: US Citizenship or Green Card required due to government contract requirements
  • $230-280,000 base + Equity + Benefits 

About the Opportunity

Our client is a rapidly growing, venture-backed AI company building secure, enterprise-grade AI solutions for highly regulated industries. Their platform helps organizations unlock the value of complex data by embedding AI into mission-critical workflows, improving decision-making, operational efficiency, and knowledge discovery.

 

As the company continues to scale, they are investing heavily in next-generation AI capabilities, including search, knowledge exploration, semantic reasoning, and agentic AI. This is an opportunity to join a high-caliber engineering team tackling technically challenging problems at production scale while helping shape the future direction of the platform.

 

The Role

As a Staff Applied Machine Learning Engineer, you will design, build, and deploy advanced machine learning solutions that power intelligent search, knowledge exploration, and AI-driven workflows.

 

You'll work closely with product, platform, and engineering teams to develop production-grade ML systems, combining strong software engineering fundamentals with expertise in modern AI techniques. This is a highly technical individual contributor role with significant ownership and influence over architectural decisions.
 

Responsibilities

  • Lead the design, development, and deployment of machine learning models for large-scale production systems.
  • Design and build intelligent search and knowledge exploration capabilities using modern ML techniques.
  • Develop systems involving knowledge graphs, semantic representations, and advanced entity understanding.
  • Collaborate with engineering and product teams to deliver end-to-end machine learning solutions.
  • Evaluate model performance, runtime efficiency, and scalability in production environments.
  • Communicate technical decisions, trade-offs, and recommendations to both technical and non-technical stakeholders.
  • Build high-quality enterprise software while maintaining a fast pace of delivery.
  • Take ownership of projects from design through implementation, deployment, and ongoing support.
  • Troubleshoot and support distributed production systems.
  • Stay current with advances in AI and machine learning and apply emerging techniques where appropriate.

Required Qualifications

  • US Citizenship or Green Card required.
  • Bachelor's or Master's degree in Computer Science, Machine Learning, NLP, or a related field. A PhD is strongly preferred.
  • 10+ years of experience building and deploying production machine learning systems.
  • Strong background in Natural Language Processing (NLP), information retrieval, or semantic search.
  • Experience designing and supporting knowledge graph or semantic representation systems.
  • Proven experience building and deploying Agentic AI systems, including orchestration, tool use, reasoning workflows, and context management.
  • Strong software engineering skills with experience building scalable distributed systems.
  • Experience working with production ML systems throughout their lifecycle.
  • Excellent communication and cross-functional collaboration skills.
  • Experience leveraging modern AI tools to improve engineering productivity.
  • Demonstrated curiosity, adaptability, and a continuous learning mindset.

Preferred Qualifications

  • PhD in Computer Science, Machine Learning, Artificial Intelligence, NLP, or a related discipline.
  • Experience working in startup or high-growth environments, particularly building 0→1 products.
  • Familiarity with Kubernetes and cloud-native infrastructure.
  • Experience integrating machine learning models into large-scale enterprise platforms.

Why Join?

  • Join a fast-growing, well-funded AI company solving complex real-world problems.
  • Work on cutting-edge technologies including Agentic AI, NLP, search, knowledge graphs, and semantic reasoning.
  • Collaborate with an experienced engineering team that values technical excellence, ownership, and innovation.
  • Competitive compensation and meaningful pre-IPO equity.
  • Fully remote position within the United States.
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