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Machine Learning Engineer, ImagesCantina • Richmond, Virginia, United States
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Machine Learning Engineer, Images

Cantina
  • US
    Richmond, Virginia, United States
  • US
    Richmond, Virginia, United States
Postuler Maintenant

À propos

About Cantina Cantina Labs is a social AI company, developing a suite of advanced real‑time models that push the boundaries of expression, personality, and realism. We bring characters to life, transforming how people tell stories, connect, and create. We build and power ecosystems. Cantina, our flagship social AI platform, is just the beginning.
If you’re excited about the potential AI has to shape human creativity and social interactions, join us in building the future!
About the Role As a Senior Machine Learning Engineer on the AI Image Generation (Imagine) team, you’ll design, implement, fine‑tune, improve and debug the image AI models that power our lifelike AI bots. The Imagine Team at Cantina is responsible for all generative image and machine vision services. Your expertise in machine learning and scalable ML infrastructure will be crucial in developing innovative features that revolutionize how people connect and create online.
AI bots on Cantina are multimodal and can text and talk with you as well as send you selfies. To provide these capabilities, we continually develop and deploy new image generation pipelines that create photorealistic, consistent characters.
The Imagine team is constantly striving to improve the quality, character consistency, responsiveness to prompting, inference time, and incorporation of an ever‑increasing number of custom looks and appearance traits.
What You’ll Do
Evaluate new image generation and identity preservation papers and models.
Develop and deploy new versions of the image generation and image analysis pipelines.
Monitor and fix production issues that impact users.
Fine‑tune and optimize models to improve character consistency, prompt responsiveness, and inference latency.
Design and run experiments to benchmark model performance, tracking quality metrics across generations of pipeline improvements.
Collaborate with cross‑functional teams to translate product requirements into ML solutions and bring new generative features from prototype to production.
What You’ll Bring
Demonstrated interest in AI image generation. This includes both personal and professional projects.
Deep technical foundation in machine learning specifically in image synthesis.
5+ years experience as a software engineer, preferably in services.
2+ years of experience building production‑grade machine learning models in industry and/or academic research settings.
Strong programming skills in Python and deploying Python based services.
Familiarity with tools and frameworks involved in AI image generation including but not limited to Stable Diffusion, Diffusion Transformers (DiT), Visual Transformers (ViT), Tensorflow, PyTorch, Diffusers, ComfyUI, TensorRT, and CUDA.
Experience building end‑to‑end scalable ML infrastructure with on‑premise or cloud platforms including Baseten, Google Cloud Platform (GCP), Amazon Web Services (AWS) or Azure.
Strong teamwork skills including communication and collaboration with both technical and non‑technical team members.
Compensation The anticipated annual base salary range for this role is between $200,000-$265,000. When determining compensation, a number of factors will be considered, including skills, experience, job scope, location, and competitive compensation market data.
Benefits We Offer
Competitive salary and generous company equity
Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina
42 days of paid time off, including:
15 PTO days
10 sick days
15 company holidays
2 floating holidays
Generous parental leave & fertility support
401(k) retirement savings plan
Lifestyle spending account – $500/month to use however you’d like
Complimentary lunch and snacks for in‑office employees
One Medical membership, and more!
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  • Richmond, Virginia, United States

Compétences linguistiques

  • English
Avis aux utilisateurs

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