Character.AI

LLM Engineer

• Lead planning and execution of major AI infrastructure initiatives spanning training pipelines, data systems, model evaluation, and inference/serving
• Build structures that keep teams aligned: scopes, goals, requirements, timelines, risks, and success metrics
• Partner with engineering, research, and product to translate model and product needs into infrastructure roadmaps and priorities
• Drive cross-functional accountability and communication across teams working on tightly coupled systems
• Track key infrastructure metrics (e.g., reliability, latency, throughput, cost efficiency) and define reporting that surfaces progress and risk
• Identify bottlenecks in infrastructure workflows and lead efforts to improve tooling, automation, and developer velocity
• Support capacity planning and resource allocation to ensure infrastructure scales with model and product growth
• Develop repeatable frameworks and operational patterns that improve execution quality across infrastructure programs
• Serve as a strategic partner to leaders on prioritization, sequencing, and tradeoffs across infrastructure investments.
• Work closely with AI cloud providers and serve as the primary bridge between internal engineering teams and external partnership efforts.
• Technical understanding of GPU clusters, AI accelerator chips, and cloud providers to effectively evaluate requirements and guide infrastructure decisions.

Technical Program Manager, AI Infrastructure

Research Engineer

• Develop and implement novel evaluation methodologies and metrics to assess the safety and alignment of large language models.
• Research and develop cutting-edge techniques for model alignment, value learning, and interpretability.
• Conduct adversarial testing to proactively uncover potential vulnerabilities and failure modes in our models.
• Analyze and mitigate biases, toxicity, and other harmful behaviors in large language models through techniques like reinforcement learning from human feedback (RLHF) and fine-tuning.
• Collaborate with engineering and product teams to translate safety research into practical, scalable solutions and best practices.
• Stay abreast of the latest advancements in AI safety research and contribute to the academic community through publications and presentations.

Research Engineer – AI Safety, Alignment

Product Designer

• Contribute to the strategic direction of our products, rooted in a desire to entertain and delight our users
• Define feature areas with excellent attention to detail and polish, identifying opportunities to improve quality and consistency of broader flows
• Craft beautiful, polished, and delightful user interfaces that build trust and showcase the power of our AI technology
• Collaborate with product managers, engineers, AI researchers and other stakeholders to define product vision, strategy and roadmaps
• Rapidly prototype ideas using code and other methods to communicate concepts and build excitement
• Find creative ways to ship high-quality work in a fast-paced, often ambiguous, resource-constrained startup environment

Product Marketing

• Lead GTM end-to-end for product launches: positioning, messaging, launch plans, cross-functional timelines, and branded campaigns
• Own the c.ai+ subscription promo calendar: plan and execute deals, discounts, and trial offers timed to brand moments, cultural moments, and product launches
• Conceive and execute branded campaigns that build awareness, drive trial, and reinforce Character’s brand with consumers
• Build and maintain the positioning framework: product positioning, competitive messaging, and value propositions that evolve with the product and market
• Monitor the competitive landscape: track competitor positioning, pricing, and marketing to inform messaging and differentiation
• Define success metrics for every launch and build repeatable playbooks from learnings
• Own app store listing performance across iOS and Android: keyword strategy, metadata optimization, conversion rate optimization, and ranking tracking
• Lead creative collaboration with the design team to ensure screenshots, preview videos, and descriptions are high-converting and brand-aligned
• Own app store promo submissions and execution: feature nominations and promotional placements with Apple and Google, aligned with the GTM and subscription promo calendars
• Own custom product page (CPP) strategy and execution: build, test, and iterate on tailored store experiences for different audiences, campaigns, and channels
• Own ASO localization across international markets: localized keywords, metadata, screenshots, and descriptions
• Set ratings & reviews strategy: define the approach for review solicitation and sentiment monitoring; partner with support to execute
• Report on ASO performance: impression-to-install conversion, keyword rankings, CPP performance, and promo impact
• Write and own conversion copy across monetization surfaces: subscription upsells, paywall modals, upgrade prompts, pricing pages, and free-to-paid nudges—hands on keyboard
• Craft the narrative arc of the free-to-paid journey: ensure every touchpoint reinforces the value of Character+ and moves users toward conversion
• Partner with Monetization PMs to translate their decisions into compelling user-facing messaging
• Run and interpret A/B tests on in-product copy to improve upgrade rates, reduce churn, and optimize conversion
• Maintain a copy system for monetization surfaces: a library of tested headlines, CTAs, and value prop messaging the team can draw from and iterate on

Product Marketing Manager

• Lead fine-tuning and continued training of video generation models, including image-to-video and joint audio-visual generation.
• Design and experiment with novel model architectures for multimodal generation, including multimodal conditioning (voice, structured text, reference images).
• Leverage techniques such as LoRA, RLHF, and full-parameter fine-tuning to improve model quality across diverse visual scenarios.
• Design and build large-scale data pipelines and automated annotation workflows to support continuous model improvement.
• Explore model compression, inference acceleration, and serving optimizations to enable efficient real-time video processing at scale.

Research Engineer, Multimodal

Full-stack Engineer

• As a Software / ML Engineer you will work cross functionally with product, data science and data platform to identify, design and implement the applied ML models and infra, ranging from the model optimization, data pipeline to model training and serving infrastructure.
• You will work on implementation of our ML backend systems to power the discovery surfaces including recommendation, ranking and search, supporting new AI generated content formats on our product while working with the team to support optimizing our existing systems.

Technical Program Manager, AI Infrastructure

Research Engineer – AI Safety, Alignment

Product Designer

Product Marketing Manager

Research Engineer, Multimodal

Software Engineer, Applied ML – Discovery, Recommendation & Search