Top Artificial Intelligence Jobs

Develop, train, evaluate, and deploy spatial generative AI models for home renovation and design. Define inference framing, prepare image-based datasets with labeling partners, iterate with user feedback, and deploy performant models into production architecture.

Lead North America enterprise sales to acquire new logos, manage complex multi-stakeholder deals with CFOs and finance leaders, build pipeline via outbound and HubSpot-driven processes, run demos end-to-end, and represent the company at industry events while scaling a high-performance sales engine.

Open application inviting exceptional candidates to apply to Asepha, an AI-driven healthcare company building tools for medication access. They seek builders who thrive in ambiguity, can ship solutions, and work cross-functionally across engineering, product, design, clinical, sales, and operations. Bonus for healthcare/pharma/regulatory or AI product experience. Offers competitive comp, equity, benefits, unlimited PTO, and in-office perks. Submissions reviewed on a rolling basis; only strong fits contacted.

Full-stack engineer responsible for building scalable Python backend services on cloud platforms, implementing real-time and streaming endpoints, managing SQL databases, integrating AI/LLM APIs (streaming), developing responsive frontends, and owning CI/CD, infrastructure-as-code, and system reliability.

Lead technical vision as a principal engineer, either managing teams or driving cross-team initiatives. Design and architect cloud infrastructure, networking, and security; define authentication/authorization patterns; architect and operate Kubernetes deployments; and implement infrastructure-as-code using tools like Terraform, CloudFormation, Ansible, or Puppet.

Build and maintain referral relationships with physicians, clinics, and community providers to drive patient referrals. Plan and execute territory outreach, host educational events, track activity in CRM, and represent Oma Fertility at local events. Travel (~50%), some nights/weekends, and collaborate with marketing to grow patient volume.

Conduct applied AI research to improve model capabilities for healthcare workflows: design evals, RL environments, benchmarks; develop and train computer-use agents; build data pipelines; publish papers; work across models, tooling, infra, and product in an on-site SF internship.

Own and maintain the backend stack: build APIs and services in Node.js, manage deployments with Docker/Linux, design scalable REST APIs with Swagger, collaborate with hardware/frontend teams, and prepare sensor datasets for AI/ML pipelines with an eventual path to Lead AI Engineer.

The GTM Lead will support enterprise deals, manage a pipeline, build a modern GTM machine using AI, and document processes in a playbook.

Develop and implement an AI-native enterprise technology platform, collaborating across teams to enhance supply chain capabilities and leading a software engineering team.