Machine Learning Engineer – Model Distillation for Real-Time 2D Image Generative A
Indexed description
Lit8 develops generative AI systems for real-time 2D image generation and enhancement. In this role, you will focus on distilling, optimizing, and deploying high-performance image generative AI models, with an emphasis on speed, quality, controllability, and production-ready performance.
You will work closely with research, engineering, and product teams to make advanced image generation models faster, lighter, and suitable for real-world applications.
Minimum Qualifications
- At least 2 years of hands-on experience distilling image generation models, preferably image-to-image models.
- Strong experience with 2D image generative AI, including diffusion models, transformer-based image models, GANs, or other generative architectures.
- Practical experience with model distillation techniques such as teacher-student training, progressive distillation, consistency distillation, adversarial distillation, feature-level distillation, score distillation, or latent-space distillation.
- Experience working with image-to-image generation tasks such as inpainting, outpainting, super-resolution, denoising, image editing, style transfer, enhancement, or controllable generation.
- Hands-on experience training, fine-tuning, evaluating, and optimizing image generation models.
- Experience improving inference latency, memory efficiency, throughput, and model quality.
- Strong programming skills in Python.
- Hands-on experience with modern ML frameworks, especially PyTorch.
- Solid understanding of model compression, mixed precision, quantization-aware optimization, pruning, or related efficiency techniques.
- Strong problem-solving, analytical, and communication skills.
- Ability to work effectively in a fast-paced, research-driven, multidisciplinary technical environment.
Preferred Qualifications
- Experience deploying optimized generative AI models into production applications, device-specific pipelines, or consumer-facing products.
- Familiarity with inference and deployment frameworks such as ONNX, TensorRT, OpenVINO, Core ML, DirectML, ROCm, Vulkan, or similar technologies.
- Experience benchmarking generative AI systems, including latency, throughput, memory usage, image quality, visual consistency, and stability.
- Experience with multimodal or foundation models for image generation, editing, enhancement, or controllable visual generation.
- Knowledge of GPU performance optimization, custom kernels, operator fusion, graph optimization, or hardware-aware model tuning.
- Contributions to open-source ML, computer vision, image generation, or model optimization projects are a plus.
- Relevant publications or research experience in generative AI, computer vision, model compression, or efficient inference are a plus.
Key Responsibilities
- Develop and apply model distillation techniques to accelerate 2D image generative AI models.
- Work on image-to-image and related generative AI workflows, including editing, enhancement, denoising, inpainting, and super-resolution.
- Improve model efficiency while preserving image quality, controllability, visual consistency, and robustness.
- Train, fine-tune, and evaluate distilled models across different image generation tasks.
- Prototype and benchmark distillation strategies across different architectures and deployment targets.
- Optimize inference performance through distillation, compression, quantization, mixed precision, pruning, graph optimization, and memory-aware tuning.
- Build evaluation workflows to measure model quality, latency, memory usage, throughput, and reliability.
- Collaborate with research, engineering, and product teams to integrate optimized models into production applications.
- Stay current with advances in image generative AI, model distillation, efficient diffusion models, and real-time inference.
What We Offer
- The opportunity to work on advanced real-time 2D image generative AI systems.
- A fast-moving, research-driven environment with real product impact.
- The chance to make state-of-the-art image generation models faster, lighter, and production-ready.
- A culture that values technical excellence, ownership, creativity, and performance engineering.
- Attractive salary.
If you are passionate about image generative AI, model distillation, and building efficient production-grade AI systems, we’d love to hear from you.
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