AI Optimization Specialist

3 days ago

India Pixis Full time

About Pixis:

Pixis is a leading US-based codeless technology company empowering brands to scale their performance marketing efforts with accessible AI. Since its inception, Pixis has been focused on developing powerful AI infrastructure that equips marketers worldwide with robust plug-and-play AI products, 200+ proprietary, self-evolving AI models without coding requirements.

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

A diverse team of over 300 members spanning 14 geographies is dedicated to building transformative AI products to optimize customers' marketing and demand generation efforts.

Explore the possibilities at https://pixis.ai/

Job Overview:

We seek an experienced AI Optimization Specialist with 3+ years of relevant experience in optimizing deep learning model performance, particularly in computer vision and natural language processing fields. The ideal candidate will have 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 the AI research and development team to integrate the latest advancements in deep learning into our projects.
  • Implement fine-tuning strategies to improve model performance on specific datasets or tasks.
  • Conduct rigorous performance testing and benchmarking to ensure models meet required 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, familiarity with TensorFlow, and understanding of deep learning architectures.
  • 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.

Salary: $120,000 - $150,000 per year, depending on qualifications and experience.

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