Enterprise Client Partner | Remote

Crossing Hurdles; United States; Remote; CAD 220,000 - 400,000; Full time

Job summary

Crossing Hurdles is looking for a full-time remote position focused on AI/ML partnerships. The successful candidate will lead technical discovery and engage with research leads and data teams to navigate system-level constraints.

This role requires strong experience in AI/ML sales, with a proven ability to close complex agreements involving data generation and evaluation.

Qualifications

• Strong relevant experience in selling into AI/ML and developer tools.
• Proven track record of closing complex, multi-stakeholder deals.
• Familiar with model evaluation and reinforcement learning.

Responsibilities

• Source and close partnerships with AI labs and ML-driven organizations.
• Lead technical discovery across evaluation workflows and model improvement.
• Translate ambiguous needs into scoped human data and evaluation programs.

Skills

Experience in AI/ML sales

Closing complex deals

Familiarity with model evaluation

Structured problem solving

Comfort in fast-moving environments

Job description

Type: Full-time

Compensation: $220K - $400K/yr

Location: Remote

Role Responsibilities

• Source and close partnerships with AI labs and ML-driven organizations focused on frontier models.
• Lead technical discovery across evaluation workflows, reinforcement learning pipelines, and model improvement loops.
• Engage directly with research leads, ML engineers, and data teams to understand system-level constraints and requirements.
• Translate ambiguous research and engineering needs into well-scoped human data and evaluation programs.
• Structure and negotiate complex, high-value agreements involving data generation, annotation, and evaluation at scale.
• Drive expansion through deeper integration into evaluation pipelines and reinforcement learning environments.

Requirements

• Have strong relevant experience in selling into AI/ML, developer tools, or deeply technical products.
• Have a strong track record of closing complex, multi-stakeholder deals with technical and commercial depth.
• Be familiar with model evaluation, reinforcement learning, or reinforcement learning from human feedback environments.
• Demonstrate a structured, hypothesis-driven approach to sales and problem solving.
• Be comfortable operating in ambiguous, fast-moving environments.