Currently tracking 10 active AI roles, down 20% versus the prior 4 weeks. Primary focus: Post-train · Engineering. Salary range $150k–$350k (avg $250k).
| Title | Stage | AI score |
|---|---|---|
| Software Engineer, AI Platform (All Industry Levels) Software Engineer on the AI Platform team at Character.AI, focusing on building tooling and datasets for model training, developing data pipelines for continuous model improvement and human feedback alignment, and supporting data infrastructure (Spark, Beam, GCP). Requires 5+ years of data engineering experience in a consumer-facing tech company, with Big Query, dbt, Ray, Beam, and Spark. | DataPost-train | 8 |
| Machine Learning Infrastructure Engineer Machine Learning Infrastructure Engineer to design, build, and maintain training and serving infrastructure for ML research, focusing on GPU allocation and utilization, cluster issue diagnosis, and deployment monitoring. | ServeData | 8 |
| Technical Program Manager, AI Infrastructure Technical Program Manager for AI Infrastructure at Character.AI, focusing on leading programs for model development and serving systems at scale. This role involves shaping infrastructure strategy, aligning roadmaps, and driving execution across training, evaluation, and inference, ensuring systems are reliable, efficient, and scalable for millions of users. The TPM will partner with engineering, research, and product teams, manage complex initiatives, track key metrics, and improve developer velocity. | ServePost-train | 7 |
| Software Engineer, Backend/Applied ML (Safety & Integrity) Software Engineer, Backend/Applied ML (Safety & Integrity) at Character.AI. Focuses on designing, developing, and scaling backend systems and applying ML to address integrity and safety challenges in human-to-AI interaction, particularly for Generative AI products. Involves content classification, anomaly detection, risk scoring, and developing safeguards. | AgentPost-train | 7 |
| Software Engineer, Applied ML (Discovery, Recommendation & Search) Software/ML Engineer to build and optimize applied ML models and infrastructure for Character.AI's consumer-facing discovery surfaces (recommendation, ranking, search), including data pipelines, model training, and serving. Focus on shipping intelligent features end-to-end. | ShipServe | 7 |
| Software Engineer, Safety Software Engineer focused on the Safety Engineering team at Character.AI. This role involves designing and building front-end experiences and tooling for Trust & Safety systems, ensuring safe user interactions with AI. Responsibilities include collaborating with product, design, and Trust & Safety operations, developing AI-assisted moderation tools, and leveraging user data to improve LLMs and AI models. The role emphasizes user experience, platform reliability, and cross-functional collaboration to define industry best practices in human-to-AI interaction. | Ship | 5 |
| Software Engineer, Core Product Software Engineer, Core Product at Character.AI, focusing on building user-friendly interfaces for their AI-powered platform. The role emphasizes front-end development, design systems, and collaboration with design and product teams to create engaging user experiences for a consumer-facing AI application. | — | 5 |
| Software Engineer, Backend Backend Engineer responsible for building and maintaining scalable, high-performance backend systems for Character.AI's consumer-facing platform. Collaborates with cross-functional teams to design and deliver robust solutions, ensuring system performance, reliability, and security. | — | 0 |
| Software Engineer, Monetization Software Engineer focused on monetization features for a consumer AI product, involving payments, subscriptions, and virtual currency systems. The role requires building and optimizing user-facing features across mobile and web, experimenting with monetization surfaces, and collaborating with design, product, and data science teams. Experience with consumer products, front-end technologies (Typescript, React), and backend services (Python, Golang) is expected, with a focus on shipping features that drive measurable outcomes. | — | 0 |