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Job Summary:
Turing is seeking an Applied Research Engineer specializing in video generation and machine learning to enhance datasets and workflows for next-generation video synthesis models. The role involves collaborating with ML teams to curate training data, contributing to model experiments, and refining workflows for high-fidelity video generation.
Responsibilities:
• Co-develop structured guidelines for datasets powering generative models, with an emphasis on:
• Prompt-conditioned video generation (text-to-video, image-to-video)
• Consistency in motion, temporal coherence, and visual quality
• Control signal labeling (e.g., camera trajectories, depth, optical flow)
• Style, identity, or scene constraints across frames
• Collaborate with ML stakeholders to align data specs with generation tasks such as video inpainting, editing, expansion, or simulation-to-real synthesis.
• Analyze where dataset limitations are causing poor outputs or failure cases in generative benchmarks (e.g., Video-Bench, VBench, or internal video synthesis metrics).
• Recommend guideline updates and synthetic data augmentations based on output inspection and metric evaluations (FID, IS, CLIP similarity, etc.).
• Assist in fine-tuning or conditioning small video generation models (e.g., diffusion-based or transformer-based architectures) under the guidance of senior engineers.
• Run targeted experiments to evaluate model behavior across data variations and prompt types.
• Build structured review protocols for evaluating generated video content, including:
• Temporal jitter or drift
• Semantic coherence with prompts
• Help define feedback loops for iterative data refinement and edge-case tracking.
• Act as a liaison between ML engineers, data operations, and evaluation teams to ensure dataset alignment with generative objectives.
• Produce clear documentation and updates on data design, annotation strategy, and model performance feedback.
Qualifications:
Required:
• 3–5 years of experience in computer vision, applied ML, or generative AI, especially with video, image, or temporal modeling.
• Familiarity with video synthesis techniques, including diffusion models, transformer-based generators, or GAN variants.
• 3+ years of experience writing production-quality software, preferably in machine learning, AI, or data science contexts.
• Proficiency in Python and familiarity with libraries such as PyTorch, Keras, scikit-learn, and Hugging Face.
• Hands-on experience with basic fine-tuning or evaluation of generative models (e.g., with PyTorch, TensorFlow, Hugging Face, or Runway).
• Exposure to tools or platforms for dataset curation and video inspection (e.g., CVAT, custom viewers, or synthetic data generators).
• Strong grasp of the data lifecycle in generative AI—annotation, prompt engineering, synthetic data usage, and evaluation.
• Ability to read ML/AI research papers (e.g., on video diffusion, text-to-video, or controllable generation) and apply insights to dataset or model design.
• Excellent communication skills —confident in presenting technical findings, coordinating with stakeholders, and translating between research and delivery teams.
Company:
Turing advances frontier AI and builds real-world systems for Fortune 500 companies, governments, and the world’s leading AI labs. Founded in 2018, the company is headquartered in Palo Alto, California, USA, with a team of 1001-5000 employees. The company is currently Late Stage. Turing has a track record of offering H1B sponsorships.
Seniority level
Seniority level
Mid-Senior level
Employment type
Employment type
Full-time
Job function
Industries
Software Development
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Medical insurance
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401(k)
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