Job Details

About the Company

Our client is a high-growth AI startup founded by former DeepMind researchers, with operations across the U.S. and Europe. The team is on a mission to push the boundaries of applied AI and deliver impactful, real-world solutions for enterprise clients.

As the company continues to scale rapidly, we're building a world-class team to support this growth and are now hiring a Solutions Engineer. This is a critical role bridging the gap between our product and our customers' data science teams.

About the Role

You'll play a hands-on role in evaluating customer data, running pilots and benchmarks, and ensuring smooth onboarding and integration.

This is a deeply technical role, ideal for someone who enjoys working with real-world data, understanding customer needs, and collaborating cross-functionally to deliver impactful AI solutions to enterprises.

Key Responsibilities

• Work with enterprise customers to understand their data, workflows, and use cases.
• Run pilot projects: test customer data on our models, validate outcomes, and tailor solutions to maximize performance and value.
• Provide technical onboarding, including deployment, configuration, and integration with customer systems.
• Collaborate with Research and Engineering to request features, tooling, and workflows that improve customer adoption.
• Work with MLOps when custom data pipelines, inference optimization, or model adjustments are required for specific customers.
• Develop reference implementations, playbooks, and best practices to streamline future customer engagements.
• Serve as the customer's advocate internally, communicating structured feedback and priorities to Product, Engineering, and Research teams.

Required Qualifications

• 5+ years of experience in Data Science, ML Engineering, or Solutions Engineering, preferably in a B2B or enterprise AI environment.
• Proven experience working with tabular/structured data, from feature engineering to model training and evaluation.
• Hands-on proficiency in Python and libraries like pandas, scikit-learn, and XGBoost/CatBoost/LightGBM.
• Strong understanding of model evaluation and cross-validation
• Excellent communication and collaboration skills, with the ability to translate technical insights into business outcomes.
• Experience with MLOps tools (MLflow, Airflow, Docker, cloud ML services) or customer-facing technical roles.
• Solid understanding of data pipelines and ETL workflows, from ingestion to model-ready datasets.
• Hands-on experience integrating data sources (APIs, databases, CSVs, or cloud storage) into ML workflows.

Benefits

• Medical, dental, and vision insurance;
• Company-provided equipment;
• Wellbeing, learning, and home office stipends;
• Team onsites in Europe;
• A mission-driven culture that values diversity of thought, humility, and bias toward action.

Please note:

This role requires significant travel across the U.S. for client implementations.

If you feel you meet the criteria and are excited to work at the intersection of AI innovation and real-world impact, we'd love to hear from you — apply now!