AI Model Optimization Specialist

3 days ago

Bengaluru, Karnataka, India Pixis Full time
About Pixis

Pixis is a pioneering codeless technology company based in the US, dedicated to developing accessible AI solutions that empower brands to scale their performance marketing efforts seamlessly. Since its inception, Pixis has been driven by a mission to create powerful AI infrastructure that equips marketers worldwide with robust, plug-and-play AI products, featuring 200+ proprietary, self-evolving AI models without requiring any coding expertise.

The company has secured $209M in total funding across Series A, B, C, and C1, backed by prominent investors including SoftBank Vision Fund, Touring Capital, Grupo Carso, General Atlantic, Celesta Capital, and Chiratae Ventures. Our esteemed customer base comprises global brands such as DHL Express, Joe & The Juice, Claroshop, Allbirds, L'Oreal, HDFC Bank, Skoda, Swiggy, Clar, and SmartAsset, among others.

Today, our diverse team of over 300 experts from 14 geographies is focused on building transformative AI products to help customers maximize their marketing and demand generation potential. Visit us at https://pixis.ai/ to discover the exciting possibilities of an AI-driven venture.

Job Summary:

We are seeking a seasoned AI Model Optimization Specialist with 3+ years of experience in optimizing deep learning model performance, particularly in computer vision and natural language processing domains. The ideal candidate will possess a strong background in software engineering, deep learning, and performance optimization techniques.

Key Responsibilities
  • Optimize deep learning model inference runtime and quality for high-performance computing environments.
  • Collaborate with cutting-edge deep learning models like Stable Diffusion, ControlNet, and LAMA, focusing on computer vision tasks.
  • Utilize inference frameworks like TensorRT, ONNX, and ONNXRuntime to accelerate and streamline model deployments.
  • Implement fine-tuning strategies to improve model performance on specific datasets or tasks.
  • Work closely with the AI research and development team to integrate the latest advancements in deep learning into our projects.
  • Conduct rigorous performance testing and benchmarking to ensure models meet efficiency and accuracy standards.
  • Provide technical guidance on best practices for deep learning model optimization and deployment.
Required Skills and Qualifications
  • Deep Learning and Machine Learning: Extensive experience with PyTorch and familiarity with TensorFlow, along with a solid understanding of deep learning architectures and efficient model implementation.
  • Inference Frameworks: Proficiency in using TensorRT, ONNX, and ONNXRuntime for model optimization and deployment.
  • Model Optimization: Strong knowledge of techniques for optimizing model inference runtime and quality, including quantization, pruning, and knowledge distillation.
  • Computer Vision Models: In-depth understanding of modern computer vision deep learning models like Stable Diffusion, ControlNet, and LAMA.
  • Software Engineering: Excellent programming skills in Python and experience in writing high-quality, maintainable code.
  • Performance Engineering: Expertise in profiling, benchmarking, and optimizing software and algorithms for maximum performance.
  • Integration: Understanding of Python API Frameworks such as FastAPI and capability to build robust and fast synchronous or asynchronous APIs, as well as experience working with queuing systems and caching systems.
  • Fine-Tuning: Knowledge of strategies for fine-tuning deep learning models to improve performance on specific tasks or datasets.
Estimated Salary Range: $120,000 - $180,000 per year

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