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.

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.

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.

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.

Manage enterprise customer relationships, drive Yext platform adoption, support retention and expansion, develop strategic success plans, identify upsell opportunities, manage renewal risks, forecast renewals, and communicate product value and roadmap insights. Partner cross-functionally with Sales, Support, Product Management, Services, and Solution Engineering while using customer analytics and digital marketing expertise to improve outcomes.

Leads end-to-end Revenue Operations across Sales, Marketing, and Customer functions. Owns forecasting, pipeline management, territory and capacity planning, performance management, operating cadences, technology architecture, and commercial decision support. The role partners with senior leaders to redesign workflows using AI and automation, improve operational leverage, and build a scalable operating system for a complex, multi-product, multi-market B2B business.

Lead integrated B2B SaaS marketing campaigns across webinars, email nurture, digital content, events, field activation, and ABM. Orchestrate campaign strategy and execution across the buyer journey, partner with Sales and Customer Success, manage marketing calendars and budgets, and use account and intent data to improve pipeline impact and conversion.

Sell commercial insurance to small business customers through inbound and outbound calls. Responsibilities include qualifying prospects, setting appointments, maintaining lead systems, understanding customer needs, partnering with underwriting, presenting policies, closing deals, and building customer relationships. The role is remote within the United States and requires strong communication, coordination, adaptability, and problem-solving skills.

Manages influencer outreach, creator negotiations, briefs, content feedback, performance tracking, contracts, payments, and gifting. Supports public relations initiatives, press events, grassroots activations, community partnerships, and marketing campaigns. Collaborates cross-functionally, analyzes campaign results, and recommends improvements to grow brand awareness.

Build and operate production AI systems for FDA regulatory intelligence, including evaluation pipelines, document ingestion and retrieval, multi-agent workflows, data pipelines, cloud infrastructure, and secure multi-tenant services. Collaborate with former FDA experts to translate domain judgment into product requirements and evaluation cases. Own architecture, reliability, observability, cost, security, and rapid 0-to-1 delivery across the stack.