Top Tech Jobs & Startup Jobs

Leads company-wide operational excellence during rapid growth, building scalable processes and coordinating Finance, Legal, People, IT, InfoSec, Compliance, and business operations. The role resolves complex cross-functional problems, supports leadership decisions, anticipates operational risks, and builds a high-performing operations team. Candidates need high-growth and global operating experience, broad ownership across multiple back-office functions, and strong people leadership. Experience in AI, data, or developer tools is advantageous.

Lead Prior Labs’ SAP partnership and go-to-market motion for TabPFN, enabling SAP sellers, shaping co-sell and commercial frameworks, managing lighthouse accounts, developing industry use cases, and extending partnerships across hyperscalers, marketplaces, and systems integrators. Own joint business and pipeline plans, reporting, and build a specialist partnerships team while working with data science and ML buyers.

Works directly with founders and the Chief of Staff to execute growth, sales enablement, automation, expansion, and people operations initiatives. Responsibilities include managing inbound pipelines, improving scoring and routing, building reporting, creating sales assets, tracking POCs, automating internal workflows across HRIS, CRM, Notion, and Slack, supporting office expansion, improving onboarding and hiring operations, and building internal tools used across the company.

Six-month Visiting Associates own a defined business function within Growth and Sales Enablement, Marketing and Community, People Operations, or Hiring. Responsibilities may include pipeline automation, reporting, social media, content production, events, onboarding, office expansion, sourcing, ATS management, and recruiting process design. Associates work directly with the founders’ office in a fast-scaling AI company and are expected to operate with high agency, structure, clear communication, and an AI-first approach.

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

As an ML Engineer, you'll deploy models and create tailored AI solutions for clients, ensuring impactful integrations and customer success.

Lead research on tabular foundation models: invent new methods and tooling, set research direction, build real-world benchmarks and datasets, implement baselines, and create automated agentic pipelines with human-in-the-loop to scale evaluation and production use.

Own day-to-day execution of the SAP partnership across technical, research, and commercial workstreams. Track commitments, coordinate engineering and research capacity, support joint scoping, co-selling, pricing, packaging, and commercial terms, and maintain accurate partnership records. Onboard SAP stakeholders, identify stalled initiatives, escalate delivery-capacity risks, and help build scalable partnership processes, playbooks, and templates.

Owns day-to-day partnerships with cloud providers, data and analytics vendors, and system integrators. Responsibilities include tracking commitments, coordinating technical resources, structuring co-sell and referral agreements, supporting pricing discussions, maintaining CRM records, aligning partnerships with sales and technical teams, onboarding partners, improving underperforming relationships, and developing scalable partnership playbooks.

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.