Top Remote Jobs in Pittsburgh, PA

The role involves building bioinformatics and ML pipelines, analyzing multi-omics data, mentoring, and collaborating across teams to develop actionable insights and scientific breakthroughs.

The Support Specialist will assist customers with Medicom's product suite, troubleshoot technical issues, and support HL7 and FHIR integrations.

Lead product marketing to define category narrative, positioning, analyst relations, go-to-market strategy, competitive intelligence, and sales enablement for Builder's AI-front-end platform, driving enterprise adoption and ROI articulation.

As an AI Engineer, you'll work closely with customers to understand their needs, train and deploy models, and build scalable AI systems.

As a Senior Data Engineer at GSTV, you will build and maintain data pipelines, ensuring data quality and collaborating with teams for scalable solutions and analytics support.

Work with B2B clients to design UGC-driven digital strategies, coach clients on UGC best practices, ideate and produce multimedia content, manage multiple client projects, serve as primary client contact, and use MarketScale tools to streamline content creation. Flexible 5–20 hours/week with occasional in-person studio/tradeshow attendance.

Lead identification and remediation of security and compliance risks, build and run a Third Party Risk Management program, ensure device and contractor environment compliance, automate processes, and support enterprise negotiations to prevent security from blocking customer acquisition.

Define and drive an AI-first platform built on proprietary GPU infrastructure. Lead product vision, roadmap, and go-to-market for GPU and distributed compute solutions. Conduct market and data analysis, partner with engineering on specifications, and collaborate across sales, marketing, and capacity teams to enable large-scale deployments and optimize utilization and deployment velocity.

Own partner integrations end-to-end: design architectures, debug code, unblock deployments, create reusable templates and automation, improve support systems, and surface product feedback to accelerate adoption.

Build and scale production-quality full-stack systems, lead cross-functional initiatives, optimize matching algorithms, create high-quality user experiences, and use experimentation and data to drive product decisions.