high-performance-computing jobs in San Diego

Senior Bioinformatics Engineer responsible for designing, building, and operating production-grade, end-to-end bioinformatics pipelines that process and interpret large-scale genome cohorts. The role involves deep expertise in genome assembly, variant calling, structural-variant calling, haplotype phasing, and pangenome analysis, with the ability to select, adapt, and benchmark state-of-the-art algorithms.…See more Requires proficiency in Python and compiled languages (C++/Rust/Go), containerization (Docker/Singularity), workflow managers (Nextflow/Snakemake/WDL), and cloud environments (AWS/GCP). The position combines applied research—exploring AI approaches for biological insight—with continuous improvement of algorithms, code, and computational infrastructure, while mentoring junior staff in a startup environment.

Senior Network Specialist supporting the High Performance Computing Modernization Program (HPCMP) with systems engineering, software development, and integration tasks. The role involves designing and integrating hardware/software solutions, conducting quality assurance reviews, developing system test strategies, and analyzing user needs to create software solutions.…See more Requires 4+ years of relevant technical experience, a BA/BS in Computer Science or related field, and intermediate-to-advanced Microsoft Office proficiency.

Build and maintain computational pipelines for sequence analysis and genotyping in HPC and cloud environments, using tools like PLINK, GATK, and BEAGLE. Perform quality control on data inputs and outputs, document work meticulously, and develop new pipelines under supervision by selecting and testing computational approaches.…See more Requires expertise in Bash scripting, bioinformatics software, Linux, cloud platforms (AWS EC2, All of Us Research workbench), and programming languages (R, Python), plus strong written and verbal communication skills.

This role combines computational research, HPC system optimization, and AI/ML deployment support at UC San Diego's Supercomputer Center. The incumbent will develop and deploy AI inference services on cutting-edge HPC platforms (PNRP, Expanse, Voyager), support researchers integrating these services into workflows, collaborate on hardware integration (FPGAs, accelerators), maintain benchmark suites on Kubernetes clusters, and contribute to proposals characterizing system performance.…See more The position requires advanced skills in HPC performance analysis, machine-learning deployment on innovative hardware, complex computing environment troubleshooting, and hands-on Kubernetes experience.

Software engineer with 6+ years of backend development experience (or 4+ with a Master's degree) designing and optimizing high-performance algorithms for radar, optical, and infrared sensor systems. You'll work with a cross-disciplinary team to engineer scalable distributed systems, accelerate code on GPUs using CUDA, and integrate scientific codebases in Linux/Unix environments.…See more Strong expertise in C/C++, high-performance computing, MPI, parallel/distributed processing, and AI/ML algorithms is required, along with advanced mathematics or physics foundations and proven system-level problem-solving ability.

Design, build, and maintain secure enterprise data platforms supporting AI/ML workloads, with responsibility for database optimization, CI/CD automation, and DoD compliance. Mentor junior engineers and provide technical leadership on architecture decisions.…See more Implement security controls aligned with NIST 800-53, RMF, and DISA STIG standards throughout the platform lifecycle. Develop ETL/ELT pipelines, support data lakes and lakehouses, and evaluate emerging data technologies for mission fit.

Design and improve autonomous AI trading systems deployed in financial markets, with core work on model architectures, training frameworks, and performance evaluation. You'll integrate novel data sources, optimize models for measurable accuracy gains and reduced training time, and build monitoring systems to detect anomalies in live trading strategies.…See more Requires strong ML fundamentals with hands-on experience in PyTorch, TensorFlow, or JAX, feature engineering, and model optimization; minimum 2 years of ML development experience preferred.

Design, implement, and optimize advanced algorithms for radar, optical, and infrared sensor systems, working with scientists and engineers to build high-performance backend systems for scientific computing in distributed environments. Translate existing code for GPU/CUDA acceleration, integrate and refactor scientific codebases, and work in Linux/Unix environments.…See more Requires 6+ years of C/C++ backend development (or 4+ with a Master's), expertise in high-performance computing, parallel/distributed processing (MPI), GPU/CUDA programming, and foundational knowledge of AI/ML and LLM concepts.

Lead Qualcomm's next-generation AI accelerator platform as senior engineering director, defining software vision, architecture, and roadmap while managing multiple engineering organizations spanning system software, device drivers, AI runtimes, compilers, ML frameworks, and platform SDKs. Partner with hardware teams on co-design, drive software readiness across chip development milestones, and establish performance/power/reliability goals.…See more Requires 9+ years software engineering experience (or PhD + 8 years), 4+ years with C/C++/Java/Python, and demonstrated expertise in AI/ML stacks, compiler technologies, runtime systems, or high-performance computing.

Sr. Director leading Qualcomm's next-generation AI accelerator platform software strategy, architecture, and delivery.…See more Manages multiple engineering organizations spanning system software, firmware, device drivers, AI runtimes, compilers, ML frameworks, SDKs, and validation. Defines performance and reliability goals, drives cross-functional hardware-software co-design, and partners with customers and hyperscalers. Requires 15+ years software engineering experience with 8+ years leading large, globally distributed teams; deep expertise in AI/ML stacks, compilers, runtime systems, or heterogeneous computing architectures.