Job responsibilities
- Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems
- Develop high-quality production level software solutions for quantum inspired algorithms.
- Write high-quality documentation and unit tests for the software solutions.
- Optimize the software solutions for execution speed, memory efficiency and communication latency through algorithmic improvements and vectorization.
- Work with the quantum-inspired algorithm researchers to identify bottlenecks in subroutines of the algorithms and devise methods to speed up the executions.
- Identify dependencies in the code to ensure seamless execution in other environments.
- Be able to benchmark the software solutions of the algorithms for any given business case against state of art solutions in the firm. Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems.
- Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development
- Be able to proactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
- Adds to team culture of diversity, equity, inclusion, and respect
Required qualifications, capabilities, and skills
- Formal training or certification on software engineering concepts with 3+ years of industry experience.
- Bachelor’s degree combined with 2+ years of industry experience in algorithm execution or a Master’s or Ph.D. degree in computer science, physics, math, engineering or related fields.
- Demonstrated ability to maintain and develop algorithm software
- Proficiency in coding in Python
- Proficient in all aspects of the Software Development Life Cycle
Preferred qualifications, capabilities, and skills
- Proficiency in C / Julia. Proficiency in C++ and Standard Template Library (STL).
- Experience with GPU acceleration and distributed programming of algorithms (CUDA, OpenCL, OpenMP, MPI, AVX).
- Experience in implementing data structures for randomized algorithms in big data settings (e.g., Sketching techniques, sampling techniques for numerical linear algebra)
- Experience in building tensor network libraries for applications in machine learning and optimization.
- Experience in running large scale Monte-Carlo simulations. Experience in accelerating annealing type algorithms using GPUs.
- Experience in using FPGAs to accelerate algorithms across machine learning or optimization.
- Experience in finance is a plus, though no prior familiarity with financial use cases is required.