Inference Specialist, Creative Technology - InterPositive

At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what’s next.The Inference Specialist, Creative Technology will report to the Sr. Director, Creative Technology and support the Production, Research, and Engineering teams working at the frontier of storytelling innovation. This role owns the practical execution of model inference workflows, translating creative needs into reproducible runs, debugging complex generation issues, and helping build reliable pipelines by turning rapidly evolving research code into reliable creative production workflows.The ideal candidate is deeply technical, operationally calm, and comfortable working in an R&D environment where models, infrastructure, datasets, and creative expectations change quickly.Responsibilities:Operate and support custom generative AI inference workflows across a wide variety of film and series projectsRun, monitor, and troubleshoot GPU-based inference jobs across local workstations, cloud infrastructure, and/or cluster environments, including distributed multi-GPU runsPrepare and validate inputs for model inference, including video, image, audio, masks, conditioning assets, prompts, metadata, and configuration filesTune inference parameters in collaboration with Creative Technology leadership, artists, researchers, and engineers to achieve production-quality resultsDebug failed or degraded runs by inspecting logs, outputs, configs, model checkpoints, data shapes, masks, frame ranges, codecs, GPU utilization, and environment issuesMaintain clean, repeatable inference launch workflows, including scripts, config templates, run manifests, output naming conventions, and result trackingPartner with researchers and engineers to test new models, checkpoints, samplers, conditioning methods, and pipeline changes in real production scenariosTranslate experimental model capabilities into usable production practicesIdentify friction in inference workflows and drive improvements through tooling, automation, documentation, and better defaultsSupport rapid iteration with artists and creative stakeholders by preparing outputs for review, comparing variations, tracking parameters, and surfacing clear recommendationsOwn quality control for generated outputsHelp bridge communication between creative, production, research, and engineering teams by explaining technical constraints and creative tradeoffs clearlyMaintain awareness of GPU capacity, queue status, runtime expectationsContribute to a culture of practical experimentation: move quickly, test carefully, document learnings, and turn one-off fixes into repeatable workflowsQualifications:4+ years of relevant experience in machine learning production, VFX technology, post-production engineering, creative technology, technical direction, or a closely related technical production roleHands-on experience running GPU-based model inference for image, video, audio, or multimodal generative AI systemsExperience working with Python-based ML codebases and command-line workflows in Linux environmentsExperience debugging production runs using logs, stack traces, configuration files, model inputs, and generated outputsWorking knowledge of deep learning inference concepts, including checkpoints, schedulers or samplers, seeds, precision, batching, conditioning, and GPU memory constraintsExperience with video and image production formats, including frame sequences, ProRes, H.264/H.265, EXR, PNG, MP4/MOV containers, resolution handling, frame rates, and colorspace considerationsExperience coordinating technical work across creative, production, research, and engineering stakeholdersDemonstrated ability to operate effectively in a fast-moving R&D environment where tools, models, and workflows change frequentlySkills:Strong practical understanding of generative AI inference workflows, especially for video, image, audio, or multimodal modelsComfort working in Linux shells, Python environments, Git repos, config files, logs, and GPU infrastructureStrong debugging instincts: able to isolate whether a problem is data, model, environment, code, infrastructure, or user configurationAbility to reason about video and tensor fundamentals, including frame counts, aspect ratios, spatial resolution, temporal alignment, masks, channels, and batch dimensionsExperience with tools and libraries commonly used in production ML workflows, such as PyTorch, CUDA, ffmpeg, OpenCV, NumPy, safetensors, and distributed launch toolsComfort with job schedulers, cloud GPU environments, or cluster workflows; Slurm experience is a strong plusCareful eye for generated output quality, including temporal artifacts, mask errors, motion issues, color shifts, compression problems, and sync problemsAble to balance creative iteration speed with technical rigor, reproducibility, and clear communicationSelf-directed and ownership-minded; comfortable seeing a messy problem, creating a path through it, and pulling in help when neededCollaborative and calm under pressure, especially when supporting time-sensitive creative reviews or production deadlinesStrong written communication, including the ability to document workflows, summarize test results, and explain technical findings to non-technical partnersComfort with ambiguity, rapidly changing tools, and incomplete informationGenuine interest in tooling for filmmakers, with the curiosity to engage deeply with both the creative possibilities and the engineering realities of the workGenerally, our compensation structure consists solely of an annual salary; we do not have bonuses. You choose each year how much of your compensation you want in salary versus stock options. To determine your personal top of market compensation, we rely on market indicators and consider your specific job family, background, skills, and experience to determine your compensation in the market range. The range for this role is $165,000.00 - $265,000.00.Netflix provides comprehensive benefits including Health Plans, Mental Health support, a 401(k) Retirement Plan with employer match, Stock Option Program, Disability Programs, Health Savings and Flexible Spending Accounts, Family-forming benefits, and Life and Serious Injury Benefits. We also offer paid leave of absence programs. Full-time hourly employees accrue 35 days annually for paid time off to be used for vacation, holidays, and sick paid time off. Full-time salaried employees are immediately entitled to flexible time off. See more details about our Benefits here .Netflix is a unique culture and environment. Learn more here .Inclusion is a Netflix value and we strive to host a meaningful interview experience for all candidates. If you want an accommodation/adjustment for a disability or any other reason during the hiring process, please send a request to your recruiting partner.We are an equal-opportunity employer and celebrate diversity, recognizing that diversity builds stronger teams. We approach diversity and inclusion seriously and thoughtfully. We do not discriminate on the basis of race, religion, color, ancestry, national origin, caste, sex, sexual orientation, gender, gender identity or expression, age, disability, medical condition, pregnancy, genetic makeup, marital status, or military service. #J-18808-Ljbffr Netflix