Requirements:

PhD or MS Degree in Computer-Science, Machine-learning, Software Engineering, or a related field
Proven experience in software development using languages such as Python and deploying applications in production systems on Kubernetes with CI/CD pipelines
Familiarity with big data technologies like Hadoop, Spark, or Kafka
Solid understanding of AI and machine learning concepts
Experience developing or AI background to develop techniques for extracting knowledge from multi-modal data, including natural language processing (NLP), computer vision, and audio analysis
Proficiency in developing and optimizing data pipelines for GPU acceleration using frameworks like CUDA, CuGraph, Rapids, TensorFlow, or PyTorch, specifically with multi-modal data
Experience with multi-modal machine learning models and techniques
Knowledge of techniques for fusing information from multiple data modalities
Experience with GPU profiling and optimization tools
Ability to work effectively in a collaborative team environment
Excellent problem-solving, analytical, and communication skills

What you'll be doing:

Design, develop, and optimize scalable software solutions and algorithms for AI applications, with a core focus on knowledge extraction and reasoning
Build, maintain, and enhance robust data ingestion and processing pipelines, with a particular emphasis on extracting latent knowledge from multiple data modalities including text, images, video, and structured data
Develop AI services (e.g., recommendation engines, fraud detection, semantic search) leveraging knowledge graphs and machine learning models
Engage in the complete project lifecycle: design, implementation, deployment, architectural reviews, and monitoring, following product team specifications
Provide high-speed prototypes and proof-of-value demos to demonstrate the value of different types of AI algorithms in unlocking value from large volumes of internal data
Participate in code reviews and uphold software development best practices, proposing improvements and adopting new technologies (e.g., graph databases, GPU frameworks) as needed
Address high-priority (P1/P0) support issues to minimize service disruptions and ensure the reliability of AI services

Opportunity to work at an innovative company changing the future of ecommerce
Joining a team of passionate thinkers, innovators, and dreamers
Collaborating with cross-functional teams for seamless integration and new feature implementation
Ownership of the complete MLOps lifecycle to push cutting-edge models and solutions