Machine Learning Solutions Engineer at fast-growing AI infrastructure startup

You will act as the primary technical bridge between commercial teams and enterprise clients, architecting complex integration paths for cutting-edge machine learning applications. By building production-quality scripts and custom proof-of-concepts, you will solve sophisticated data pipeline challenges and serve as a key technical advisor to engineering leaders during the high-stakes evaluation process.

Fast-growing AI infrastructure startup

• Lead technical discovery and architecture strategy for complex enterprise sales cycles to ensure successful platform integration.
• Build and deploy robust Python-based proof-of-concepts that handle sophisticated data ingestion and custom workflow requirements.
• Guide prospective technical stakeholders through security, infrastructure, and architectural evaluations for large-scale machine learning deployments.

• Has 2-3+ years of experience in a technical, customer-facing role such as Solutions Engineering or Architecture within the AI sector.
• Possesses strong hands-on coding skills in Python and deep familiarity with modern cloud infrastructure like AWS, GCP, or Azure.
• Demonstrates a "hacker mindset" to creatively solve integration hurdles while maintaining a focus on scalable, production-quality engineering standards.

• Work at the forefront of the AI boom by solving the critical data quality bottlenecks that prevent modern models from reaching production.
• Join a high-growth environment backed by top-tier Silicon Valley VCs that has doubled its headcount in the last year due to massive market demand.
• Influence the core product roadmap by acting as the primary feedback loop between elite enterprise engineering teams and internal developers.