Top Artificial Intelligence Jobs

Own and grow a portfolio of Canadian client accounts as the senior relationship lead. Responsibilities include account planning, renewals, expansions, cross-selling, executive stakeholder engagement, revenue forecasting, client satisfaction, business reviews, and collaboration with delivery and studio teams. The role also provides market insight, strengthens client partnerships, coaches account management practices, and drives sustainable revenue growth while maintaining service quality and organizational values.

Build and scale AI/ML solutions for healthcare revenue cycle automation. The role owns AI outcomes, identifies high-value use cases, shapes technical and product roadmaps, converts prototypes into scalable production systems, and architects infrastructure for training, testing, monitoring, security, and deployment. The engineer will apply ML, NLP, and LLM approaches to claims and workflow optimization while balancing technical tradeoffs, business value, cost, and operational efficiency.

Own Civic Marketplace’s commercial and operational engine as a hands-on, near-cofounder-level leader. Responsibilities include connecting product, operations, and commercial teams; managing dashboards, reporting, and performance; owning P&L and business outcomes; developing the business model; setting priorities; building public-sector customer trust; and hiring and coaching leaders. The role requires strong quantitative judgment, early-stage operating experience, pragmatism, and comfort with ambiguity.

Freelance writers summarize recent machine learning research papers for The Batch, an AI newsletter reaching over two million professionals and students. Writers must understand machine learning technology, explain complex research clearly in an established format, and communicate effectively in English. The role is intended for graduate students and postdocs in machine learning, with negotiable freelance compensation.

General application for future opportunities at a remote open-source consulting company. Potential work includes software engineering, scientific computing, AI/ML, data engineering, DevOps, developer tooling, frontend development, technical writing, design, and community engagement. Quansight welcomes professional, research, educational, personal-project, and open-source experience, including early-career and internship interest.

Own product requirements and development for robot data collection systems. Lead hands-on prototyping, benchmark cameras and other components, and drive hardware/software integration across sensing, calibration, and synchronization. Track technical issues, validation, schedules, and delivery while collaborating with Research, Data, engineering, manufacturing partners, and global factories. The role requires strong hardware and software adaptability, bilingual Mandarin-English communication, and occasional travel.

Build and own production data pipelines, warehouse models, metric definitions, testing, monitoring, reconciliation, and alerting. Partner with Finance and other teams to create reliable datasets for usage, revenue, costs, margins, reporting, self-service analysis, and AI-assisted querying. Improve source data quality, investigate discrepancies, and establish a maintainable data foundation.

Own high-priority founder-led projects across product, sales, hiring, and operations. Responsibilities include launching new initiatives from scratch, supporting client and market activities, building prototypes, organizing events, and taking projects end-to-end with high autonomy. The role is onsite in San Francisco and may develop into a full-time position in Deployment, Growth, or Special Projects.

Generate qualified pipeline through account research, cold calling, personalized email, LinkedIn outreach, and social selling. Qualify inbound and outbound leads, conduct discovery calls, book meetings for account executives, and provide smooth handoffs. Own activity KPIs and pipeline targets while collaborating with Sales and Marketing to improve messaging and outreach. Maintain product and industry knowledge in a fast-moving AI startup environment.

Administer and optimize IBM Db2 for z/OS production databases, including design, performance tuning, security, backup and recovery, utilities, upgrades, and disaster recovery. Support SQL Server, Azure SQL Managed Instance, data movement pipelines, DDF/DRDA connectivity, and ITIL operations. Maintain documentation, runbooks, audit support, and recovery procedures while mentoring developers and cross-training backup administrators. Participate in on-call rotations and collaborate across mainframe, data engineering, warehouse, application, and systems programming teams.