Senior System Software Engineer, ML, Vector Search

This is a fully remote position, open to applicants in California.

📋 Description

• Analyze, design, and implement optimized algorithms for GPU aimed at large-scale vector searches, databases, and machine learning applications.

• Conduct performance analysis, benchmarking, and optimization of related libraries.

• Collaborate with a diverse team to comprehend requirements and enhance or develop solutions.

• Enhance and develop machine learning algorithms.

• Implement solutions using C++, CUDA, and Python.

• Contribute to open-source projects such as cuML, cuVS, and RAFT.

• Research, develop, benchmark, and investigate innovative custom algorithms for vector preprocessing, indexing, search, clustering, and visualization.

• Work closely with engineers to enhance vector search, database, and machine learning functionalities.

⛳️ Requirements

• BS, MS, or PhD in Computer Science, Data Science, AI, Applied Mathematics, or a related field (or equivalent experience).

• Over 8 years of programming experience in C++ or the ability to transition from a similar programming language such as C, Rust, or Java.

• Proficiency with machine learning concepts, developing ML algorithms, and applying ML to solve real-world problems.

• Strong analytical and problem-solving skills, along with a solid foundation in algorithms and mathematics.

• Exceptional software development capabilities, including programming, debugging, performance analysis, and test design.

• Ability to work autonomously and manage your own development projects.

• Effective communication and documentation practices.

• Dedication to producing robust, readable, and high-performance code.

• Familiarity with at least one parallel programming or concurrency framework, such as CUDA, OpenMP, OpenACC, Java concurrency, or pthreads.

• Experience in developing distributed algorithms and operating within distributed systems like HPC or Cloud (preferred).

• Strong debugging skills for complex systems involving multiple programming languages and hardware (preferred).

• Knowledge of vector databases and nearest-neighbor algorithms such as Milvus, Pinecone, LanceDB, as well as graph and IVF indexes (preferred).

• Background in machine learning, including clustering, dimensionality reduction, probability and formal methods, and applied research (preferred).

• Experience in GPU programming is a plus.

🏝️ Benefits

• Competitive salary package.

• Equity options.

• Comprehensive benefits.