ML Engineer

Crossing Hurdles is a global recruitment firm partnering with a fast-growing AI-powered recruiting marketplace modernizing how companies hire. Backed by top-tier investors and trusted by industry leaders like Palantir, Shopify, and Coinbase, is building the first end-to-end AI recruiting marketplace that combines specialized recruiters with AI agents to help companies hire faster and more accurately.

Role: ML Engineer

YOE: 4+ years of experience in data engineering, deploying security-sage ML solutions

Location: Washington DC, DMV Area | Hybrid

Compensation: $150K – $215K

Roles & Responsibilities

• Lead enhancements to the Virtualitics AI Platform to ensure innovation, performance, and reliability.
• Build and maintain interactive dashboards using the Virtualitics Python SDK.
• Optimize data pipelines and access patterns for scalability and efficiency.
• Troubleshoot performance issues to ensure low latency and high availability.
• Design scalable, production-ready AI solutions.
• Collaborate with engineering and product teams to deploy ML models.
• Contribute across ML, data engineering, and software development.

Requirements

• 4+ years of experience in data engineering, deploying security-sage ML solutions
• Willingness and eligibility to obtain U.S. Government security clearance
• CS degree from top 100 schools
• Strong programming skills in Python(panda) and experience with ML libraries such as PyTorch, TensorFlow, and scikit-learn
• Hands-on experience building, training, evaluating, and deploying machine learning models into production
• Understanding of data engineering concepts including data pipelines, ETL workflows, and optimizing data access patterns

Why Candidate Should Join

• Work on cutting-edge AI and GenAI systems using LLMs, Reinforcement Learning, and modern ML frameworks in production environments.
• Own ML features end to end, from experimentation and training to deployment and optimization.
• Deliver high-impact work that directly influences users and business outcomes.
• Learn and grow quickly while deepening expertise in applied ML and scalable AI systems.
• Thrive in a flexible, modern work environment that values autonomy and results.