Staff Applied Machine Learning Engineer

yurtsai; United States; Remote; USD 200,000 - 240,000; Full time

Benefits offered by this job

Remote within USA

Competitive salary $200k–$240k USD

Equal opportunity employer

Job summary

yurtsai is seeking a senior ML engineer to lead the design, development, and deployment of ML and algorithmic solutions powering enterprise-grade products. You will own ML systems end-to-end, collaborating with product and platform teams to deliver scalable, reliable solutions.

Candidates should have 10+ years of ML experience, expertise in knowledge graphs, and experience with Agentic AI systems. This role is remote within the United States and offers a strong compensation package.

Qualifications

• 10+ years of ML engineering experience building large-scale systems.
• Hands-on with knowledge graphs and semantic representations.
• Experience designing Agentic AI systems with reasoning loops.
• Ability to communicate across cross-functional teams.
• Comfort maintaining production distributed systems.
• Growth mindset and collaboration.

Responsibilities

• Lead the development of machine learning models and data-driven algorithms for high-impact projects.
• Design and build complex systems involving knowledge graphs and advanced entity detection.
• Collaborate with product and platform teams to own ML solutions end-to-end.
• Reason about runtime complexity and production cost of running ML models at scale.
• Communicate modeling decisions, tradeoffs, and limitations clearly to technical and non-technical stakeholders.
• Build, deliver, and maintain enterprise products that meet high-quality standards while shipping quickly.
• Support production systems, debug distributed systems, and ensure reliability and uptime.

Skills

ML engineering

Knowledge graphs

Agentic AI

Production systems

Cross-functional collaboration

Communication

Distributed systems

Education

Bachelor's/Master's in CS/ML/NLP (PhD preferred)

Tools

Kubernetes

AI tooling

Job description

Role overview

This senior role leads the design, development, and deployment of machine learning and algorithmic solutions that power high-impact, mission-oriented products. The position blends deep technical leadership with cross-functional collaboration, owning ML systems end-to‑to‑end while supporting production environments that operate at enterprise scale.

Responsibilities

• Lead the development of machine learning models and data-driven algorithms for high-impact projects
• Design and build complex systems involving knowledge graphs and advanced entity detection
• Collaborate with product and platform teams to own ML solutions end-to‑end
• Reason about runtime complexity and production cost of running ML models at scale
• Communicate modeling decisions, tradeoffs, and limitations clearly to technical and non-technical stakeholders
• Build, deliver, and maintain enterprise products that meet high-quality standards while shipping quickly
• Support production systems, debug distributed systems, and ensure reliability and uptime

Requirements

• US Citizenship or Permanent Residency required due to government contract work; must be domiciled in the US
• Bachelor's or Master's degree in Computer Science, Machine Learning, or NLP (PhD preferred)
• 10+ years of ML engineering experience with a proven track record of building models for large-scale systems
• Hands-on experience building and supporting knowledge graph and semantic representation systems
• Proven experience designing, evaluating, and optimizing Agentic AI systems, including reasoning loops, tool use, orchestration patterns, and context management
• Strong communication skills and effectiveness collaborating across cross-functional teams
• Comfort supporting production systems and debugging distributed systems
• Demonstrated effectiveness using AI tooling to accelerate research and development workflows
• Growth mindset with low ego and a drive to foster collaboration, psychological safety, and technical excellence

Nice to have

• Start-up experience or comfort in 0→1 product environments
• Familiarity with Kubernetes
• Experience integrating ML models and data-driven algorithms into larger system architectures

Benefits and work setup

• Remote position within the USA
• Compensation: $200,000—$240,000 USD
• Equal opportunity employer with comprehensive protections against discrimination and harassment