Top Tech Jobs & Startup Jobs

Own and build the company’s machine learning infrastructure, including a shared feature store, model-serving systems, drift monitoring, and unified deployment pipelines. Establish long-term MLOps standards and processes from the ground up, while collaborating with data scientists and engineers to drive adoption and improve production model reliability.

Build, configure, administer, and maintain Salesforce solutions supporting go-to-market teams. Translate business requirements into scalable technical designs, manage users and access controls, troubleshoot production issues, support integrations and multi-org initiatives, document configurations, and participate in testing, quality assurance, change management, and SOX-compliant releases. Collaborate with cross-functional stakeholders and external partners while communicating technical information and project risks clearly.

Lead design and delivery of full-stack basketball scoring, statistics, and postgame features. Build scalable backend services and APIs with TypeScript and Node.js, develop React web experiences, support iOS and Android products, and make architectural decisions. Collaborate across product, design, and engineering teams, ensure code quality and system reliability, mentor peers, and contribute to technical standards and tools.

Analyzes complex data, fraud trends, market needs, and customer insights to guide product strategy, innovation, go-to-market decisions, and revenue growth. Develops analytical frameworks, proofs of concept, and fraud solution pilots; researches emerging attack methods; and translates findings into recommendations for cross-functional technical, product, commercial, and operational stakeholders. The role also supports sales enablement, customer conversations, and product investment decisions.

Own the Americas B2B CRM roadmap for Wise Business, driving acquisition, switching, onboarding, activation, and customer value. Partner with Sales, Marketing, Brand, and Analytics to build lead-generation and nurture programs, adapt regional content, and deliver email, push, and in-app campaigns. Manage segmentation, personalization, experimentation, QA, deliverability, stakeholder coordination, and performance analysis across North and Latin American markets.

Own the marketing operations infrastructure supporting GC AI’s funnel from education and trial signup through paid conversion and expansion. Responsibilities include marketing technology architecture, HubSpot and Salesforce administration, lead scoring and routing, attribution, pipeline reporting, campaign operations, conversion optimization, ABM execution, data quality, compliance, automation, documentation, and project management.

Drive new business sales for mid-market companies operating 50–175 trucks across the US and Canada. Own the complete sales cycle, including prospecting, outbound outreach, discovery, demonstrations, trials, negotiation, closing, forecasting, and quota attainment. Collaborate with sales development, sales engineering, and customer success teams while maintaining strong KPI performance and developing customer relationships.

Lead a team of software engineers building and scaling Spark’s broker productivity platform. Responsibilities include architecting full-stack solutions, guiding technical direction, reviewing code, managing infrastructure priorities, coordinating product planning, sequencing projects, coaching engineers, hiring, and ensuring reliable, high-quality delivery. The role balances hands-on engineering with people management and is fully remote within the United States.

Build and deploy AI-native products that transform large-scale geospatial data into actionable intelligence. Design multi-agent workflows, integrate frontier LLMs, engineer tool-using agents, and develop data pipelines for anomaly detection and predictive analytics. Ensure secure, scalable cloud integrations and operate production AI systems using DevOps, containerization, orchestration, and CI/CD. Establish feedback and reinforcement mechanisms to improve model reliability while contributing to AI-first engineering standards and documentation.

Manage AI and machine learning products for materials science, including customer demonstrations, roadmap planning, product expansion, ML model development, and leadership of the materials science ML team. The role requires deep expertise in materials science and ML, software-industry experience, customer engagement, public presentations, and global travel.