Machine Learning Engineer, Images
Designs, fine-tunes, and deploys image generation models for photorealistic AI bots, optimizing for consistency, latency, and quality. Requires 5+ years software engineering, 2+ years production ML, and expertise in diffusion models like Stable Diffusion and PyTorch.
About the job
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 (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
- Anticipated annual base salary range: $200,000-$265,000
Skills
PyTorch, TensorFlow, Stable Diffusion, Diffusers, Kubernetes, Python, CUDA, TensorRT, GCP, AWS
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