Post Producer: (Feature Film) Location: NYC/LA/London Employment: Contract About Wonder Studios We are an AI native creative studio building performance centric, productionised pipelines for ambitious short and feature projects. We combine traditional VFX craft with emerging AI-driven techniques to reduce cost, speed up iteration and preserve high quality finish. Role summary We are hiring a senior Post Producer to lead bidding, budgeting and workflow design for a VFX-heavy feature films. The role will define a repeatable, productionised approach that blends AI-driven processes with conventional comp, roto, 3D and cleanup. You will own the commercial and operational delivery model for VFX across pre-production and post. Key responsibilities Lead VFX bid and budget creation for feature film scope • Break down sequences and shots, produce detailed shot lists and task lists suitable for vendor and internal costing • Translate creative VFX requirements into realistic vendor scopes, staffing plans and delivery milestones Must have Significant experience bidding and producing VFX for feature films with demonstrable credits on VFX heavy features • Strong track record producing accurate, defensible feature-level VFX budgets and vendor bids • Hands on experience with shot breakdowns, vendor costing and creating productionised workflows for complex VFX projects • Proven vendor management and negotiation experience across comp, roto, 3D and cleanup vendors • Practical familiarity with post tracking tools such as ShotGrid, Nuke, Maya, Houdini or equivalent pipelines • Excellent stakeholder communication and the ability to present budgets and workflow proposals to producers and financiers Nice to have Practical understanding of AI-enabled workflows and tools used in image and video generation, enhancement or automation • Experience integrating AI processes into a VFX pipeline • Experience working with distributed editorial and VFX teams, remote review platforms and high throughput delivery models • Experience with cost per minute or cost per shot pricing frameworks for features

• Develop and deploy AI chatbot/agent solutions for enterprise use cases • Integrate LLM-based agents with structured and unstructured enterprise data • Connect chat interfaces to SQL/enterprise databases and internal APIs • Build and integrate machine learning models (prediction, classification, clustering, etc.) • Perform data preprocessing, feature engineering, and model evaluation • Integrate ML outputs into chatbot or workflow interfaces • Support data pipeline development and automation • Collaborate with internal team and occasionally clients to understand requirements • Document model logic, workflows, and implementation details

• Own the design, development, and deployment of robust machine learning solutions to solve cross-cutting problems within the fashion resale space • Work with and fine-tune models for representation learning, computer vision, and classification, and own efforts to productionize, scale, and evolve them as shared systems • Partner closely with senior stakeholders across the business to define problems, and lead the design of general-purpose, scalable ML solutions that power features like content understanding, moderation, and personalisation • Lead the end-to-end lifecycle of large-scale experiments, from hypothesis generation through evaluation, to guide model and product improvements, ensuring statistical difficulty and real-world applicability • Stay up to date with research, actively contribute to internal knowledge sharing and ML best practices, and chip in technical expertise to long-term product and data strategy • Participate in team ceremonies, such as agile cadences, technical whiteboarding sessions, and planning/roadmapping, setting technical direction and improving for the team • Communicate technical findings clearly and confidently to both technical and non-technical audiences, including senior stakeholders, and influence decision making

• Build Core Platform Features: Develop backend services, APIs, and user-facing features across the platform. You'll work on everything from symptom tracking to lab result visualization to treatment recommendations. • Integrate Data Sources: Build integrations with wearables (Oura, Apple Health, Whoop, Garmin), lab providers, and other health data sources. Create pipelines that ingest, normalize, and store data reliably. • Contribute to AI/ML Systems: Work alongside senior engineers to build and improve our health intelligence engine—including conversational AI, recommendation models, and pattern detection. Prior ML exposure is helpful; willingness to learn is essential. • Ship Fast and Iterate: We're early stage. You'll ship code frequently, get feedback from real users, and iterate quickly. Comfort with ambiguity and a bias toward action are key. • Build with AI-Native Tools: Use Claude, Claude Code, Cursor, and other AI-assisted development tools daily. We embrace vibe coding and expect you to leverage AI to move faster and learn faster. • Learn the Healthcare Domain: You'll pick up health data concepts, compliance basics (HIPAA), and clinical terminology as you go. We'll support your learning—curiosity matters more than prior experience here.