Top Tech Jobs & Startup Jobs

Own end-to-end hiring for US go-to-market and operations teams: source enterprise sales, partnerships, finance, and compliance talent; run structured interviews with clear rubrics; manage ATS pipeline and weekly metrics; negotiate and close offers including variable comp and equity; coordinate multi-hub (US/EU) hiring, relocation, and visa considerations.

Own end-to-end hiring for US go-to-market and operations functions: source and assess enterprise sales, partnerships, finance, and compliance talent; run structured interview loops, manage ATS pipeline and metrics, negotiate offers including variable comp and equity, and coordinate multi-hub US/EU hiring and occasional relocation/visa work.

Own and consolidate Prior Labs' partner portfolio, manage the SAP strategic relationship, qualify and generate non-SAP partner-led revenue, sign and run integrations/reseller and co-marketing partnerships, and build partner playbooks, co-sell processes, enablement, and reporting. Start as an individual contributor and scale a partnerships team.

Drive commercial adoption of foundation models for structured data through outbound outreach, sales cycle ownership, and technical engagement. Shape sales strategies and materials while managing key buyer relationships.

As the first Partner Manager, you'll manage day-to-day partnerships, coordinate with teams, structure agreements, and develop new partner relationships to drive growth.

As a Data Scientist, you'll bridge cutting-edge AI models with real-world applications, driving experimentation, customer success, and education while showcasing TFM value through PoCs and workshops.

Design, build, and scale core infrastructure for machine learning models, manage production systems, and implement best practices in MLOps.

Provide end-to-end legal ownership for an early-stage AI company: commercial contracts, IP and open-source strategy, data privacy, post-acquisition governance, manage external counsel, and build scalable legal systems and templates.

Lead company-wide operations, build scalable processes, partner with finance, people, legal, IT/InfoSec and compliance, resolve cross-functional issues, and grow an operations team to support rapid global scaling.

The Senior ML Infrastructure Engineer will own and optimize GPU infrastructure for training tabular foundation models, ensuring high efficiency and collaboration with research teams.