LIT8
Machine Learning Engineer – AMD Device Deployment for Real-Time 2D Image Generative AI
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Machine Learning Engineer – AMD Device Deployment for Real-Time 2D Image Generative AI
ML Engineer (AI Infrastructure - Image Generation) — Lit8
Lit8 develops generative AI systems for real-time 2D image generation and enhancement on AMD devices. In this role, you will optimize and deploy high-performance image generative AI models, with a focus on low-latency inference, model efficiency, and production-ready performance across AMD hardware platforms.
You will work closely with engineering, product, and platform teams to bring advanced image generation models into real-world applications, ensuring they run efficiently, reliably, and at scale.
Minimum Qualifications
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Education:
- Ph.D. in Computer Science, Mathematics, Electrical Engineering, or a related field; or,
- Master’s degree with 2+ years of relevant industry experience; or,
- Bachelor’s degree with 4+ years of relevant industry experience.
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Experience & Technical Skills:
- 2+ years of hands-on experience optimizing machine learning models on AMD devices or AMD-compatible hardware/software stacks.
- Strong expertise in machine learning, deep learning, neural networks, and generative AI models.
- Hands-on experience with modern ML frameworks such as PyTorch, TensorFlow, JAX, or ONNX-based workflows.
- Advanced programming skills in Python.
- Solid understanding of model training, evaluation, optimization, and deployment.
- Experience improving inference performance, memory efficiency, and latency.
- Strong problem-solving, analytical, and communication skills.
- Ability to work effectively in a fast-paced, multidisciplinary technical environment.
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Preferred Qualifications
- Experience with:
- 2D image generative AI (e.g., text-to-image, image-to-image, inpainting, outpainting, super-resolution, denoising, image editing, style transfer, or real-time image enhancement).
- Optimizing models through quantization, pruning, distillation, mixed precision, graph optimization, operator fusion, memory optimization, or custom kernels.
- GPU programming or performance tuning experience using HIP, Triton, Vulkan Compute, OpenCL, or similar technologies.
- Experience integrating ML models into production applications, device-specific pipelines, or consumer-facing products.
- Contributions to open-source ML, computer vision, image generation, or systems projects are a plus.
Key Responsibilities
- Develop, optimize, and deploy real-time 2D image generative AI models for AMD devices.
- Build efficient inference pipelines for production use across AMD hardware targets.
- Convert, profile, and optimize models using ONNX, ROCm, HIP, MIGraphX, DirectML, Vulkan Compute, or related technologies.
- Improve model performance through quantization, mixed precision, graph optimization, operator fusion, memory optimization, and hardware-aware tuning.
- Optimize image generation and enhancement models for speed, quality, responsiveness, and reliability.
- Benchmark performance across AMD device configurations, measuring latency, throughput, memory usage, image quality, and stability.
- Collaborate with engineering, product, and platform teams to integrate AI models into production applications.
- Stay current with advances in generative AI, 2D image models, model optimization, and AMD deployment technologies.
- Work cross-functionally to ensure technical solutions align with product and business goals.
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What We Offer
- The opportunity to work at the intersection of real-time 2D image generative AI and AMD device deployment.
- A fast-moving, research-driven environment with real product impact.
- The chance to optimize and deploy next-generation image generation models on modern AMD devices.
- A culture that values technical excellence, ownership, creativity, and performance engineering.
- Attractive salary.
If you are passionate about generative AI, image generation, model optimization, and high-performance deployment on AMD platforms, we’d love to hear from you!
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