Job description

Crazy Maple Studio is a rapidly growing entertainment and technology company with offices in the San Francisco Bay Area and Los Angeles. We specialize in mobile gaming, digital reading, and streaming, bringing together a global team to create innovative, engaging entertainment experiences for audiences worldwide. Our flagship platform, ReelShort , is a leading vertical streaming app in the U.S., with more than 8 million daily active users (DAU). Through its short-form episodic content, ReelShort delivers compelling stories designed for today’s mobile-first audiences. Our portfolio also includes Chapters , an interactive storytelling platform featuring immersive drama, fantasy, and romance experiences, and My Fiction , a platform dedicated to discovering and creating serialized romance stories. In 2025, Crazy Maple Studio was recognized as one of the Global Most Loved Workplaces , reflecting our commitment to fostering a culture that values creativity, innovation, collaboration, and employee well-being. At Crazy Maple Studio, we’re passionate about pushing creative boundaries, exploring new possibilities in digital entertainment, and building experiences that connect with audiences around the world. Position Overview: We’re looking for builders. We don’t want ticket-closers, and you won’t need a 40-page spec. We’re putting together a small vanguard team, led directly by our executive team, with one mission: find out what AI can really do for entertainment, then ship it. ReelShort already entertains millions of people around the world. This team works outside the normal roadmap. You might take an idea on Monday, have a working demo by Friday, and put it in front of real users soon after. Some experiments will fail fast. The ones that work could become the company’s next big product. If you’ve been waiting for a place where your work gets seen, your judgment is trusted, and your growth isn’t capped by a ladder, this is it. Why This Team: • You work directly with the leadership. There are no layers. Your ideas get heard, and your work is seen by the person who makes the call. • Zero-to-one, every time. You build new things instead of maintaining old ones. • Help shape the stack. This is a brand-new team with no legacy code. The tools we choose now are the ones we’ll scale on, and you’ll help choose them. • AI is the job, not a side project. You’ll use the newest models and tools every day, and you’ll be paid to explore what comes next. • Real ownership. You own what you build, from the first line of code to the user metrics after launch. • We invest in your future here. We offer sponsorship for strong performers. Responsibilities: • Design and build the backend systems behind new AI-powered apps, from first prototype to serving real users at scale • Help choose and set up our stack, from languages and databases to deployment and CI/CD • Connect large language models (OpenAI, Anthropic, Gemini, or open-source) to our products through a unified gateway, so we can switch models, control costs, and track spend by feature • Build the APIs our mobile apps depend on, along with the data foundations that show us what’s working • Own reliability for the services you build: monitoring, debugging, and fixing what breaks • Try new AI infrastructure and research, and turn what you learn into proposals • Around 2–5 years of experience building backend systems that real users depend on • Strong in at least one backend language, such as Python, TypeScript (Node.js), Go, or Java • Solid experience with relational databases (PostgreSQL, MySQL, or similar), plus caching and queues (Redis, SQS, Pub/Sub, or similar) • Deployed services on AWS or GCP using containers or serverless (ECS, Cloud Run, Lambda, or similar), and set up CI/CD (GitHub Actions or similar) • Kubernetes experience is not required. We keep infrastructure lean at this stage • Daily user of AI coding tools, with the drive to go much deeper • Fast learner who moves quickly and is comfortable with ambiguity • Self-directed, low ego, and willing to do the unglamorous work a zero-to-one product needs • Hands-on experience with LLM APIs, RAG, vector databases, or agent frameworks a plus • Experience with LLM gateways (such as LiteLLM) or tracking inference costs a plus • Infrastructure-as-code experience (Terraform, Pulumi, or similar) a plus • Experience with media pipelines or AI image, video, or audio generation a plus • Experience with machine learning or model fine-tuning a plus • Additional language capability (Mandarin) a plus, though not required Immigration Support • H-1B transfers welcome • On OPT or STEM OPT? We’ll register you for the H-1B lottery • Green card sponsorship for strong performers • Legal and filing fees are covered by the company How We Hire Four steps, with no marathon onsite: • Intro call • Take-home technical exercise • Technical interview • Conversation with our CEO Logistics • Five days a week, onsite in Sunnyvale, CA • Occasional evening availability to sync with teams in other time zones Crazy Maple Studio, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. Our target salary range for this role is between $120,000 and $150,000 . Actual starting salary within the range will depend on various considerations, including: work experience, skills, specializations, and training. This role also offers medical insurance, a 401(k) retirement plan, and a range of additional employee benefits and perks.

Requirements

Must-haves

In 2025, Crazy Maple Studio was recognized as one of the Global Most Loved Workplaces , reflecting our commitment to fostering a culture that values creativity, innovation, collaboration, and employee well-being.
At Crazy Maple Studio, we’re passionate about pushing creative boundaries, exploring new possibilities in digital entertainment, and building experiences that connect with audiences around the world.
If you’ve been waiting for a place where your work gets seen, your judgment is trusted, and your growth isn’t capped by a ladder, this is it.
You work directly with the leadership. There are no layers. Your ideas get heard, and your work is seen by the person who makes the call.
Zero-to-one, every time. You build new things instead of maintaining old ones.
Help shape the stack. This is a brand-new team with no legacy code. The tools we choose now are the ones we’ll scale on, and you’ll help choose them.
AI is the job, not a side project. You’ll use the newest models and tools every day, and you’ll be paid to explore what comes next.
Real ownership. You own what you build, from the first line of code to the user metrics after launch.
We invest in your future here. We offer sponsorship for strong performers.
Design and build the backend systems behind new AI-powered apps, from first prototype to serving real users at scale
Help choose and set up our stack, from languages and databases to deployment and CI/CD
Connect large language models (OpenAI, Anthropic, Gemini, or open-source) to our products through a unified gateway, so we can switch models, control costs, and track spend by feature
Build the APIs our mobile apps depend on, along with the data foundations that show us what’s working
Own reliability for the services you build: monitoring, debugging, and fixing what breaks
Try new AI infrastructure and research, and turn what you learn into proposals
Around 2–5 years of experience building backend systems that real users depend on
Strong in at least one backend language, such as Python, TypeScript (Node.js), Go, or Java
Solid experience with relational databases (PostgreSQL, MySQL, or similar), plus caching and queues (Redis, SQS, Pub/Sub, or similar)

Nice-to-haves

Hands-on experience with LLM APIs, RAG, vector databases, or agent frameworks a plus
Experience with LLM gateways (such as LiteLLM) or tracking inference costs a plus
Infrastructure-as-code experience (Terraform, Pulumi, or similar) a plus
Experience with media pipelines or AI image, video, or audio generation a plus
Experience with machine learning or model fine-tuning a plus
Additional language capability (Mandarin) a plus, though not required

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aici/cdpythontypescriptnode.jsgojavaawsgcpkubernetesllmmachine learning

Platform: workable
Effort: medium

Benefits

Benefits detected in the listing.

401(K)