
501 - 1000 employees
Founded 2006
đł Fintech
đ€ Artificial Intelligence
đ€ B2B
Fintech âą Artificial Intelligence âą B2B
SPD Technology is a global software product development company that delivers custom digital platforms, cloud and DevOps, AI/ML, and fintech/payment solutions. They specialize in application modernization, data analytics and engineering, system integration and APIs, security and quality engineering, and mobile/web UX/UI development. SPD works as a B2B partner for enterprise and growth-stage clients (notable customers cited include PitchBook and Poynt), focusing on building payment systems, billing and fraud-detection software, data platforms, and AI-enabled products for industries such as fintech, insurance, healthcare, and e-commerce.
đ„ 3 minutes ago
đ United Kingdom, Colombia, +4 more countries â Remote
â° Full Time
đ Senior
đ» Solutions Engineer
đ» Ghost score 10%
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501 - 1000 employees
Founded 2006
đł Fintech
đ€ Artificial Intelligence
đ€ B2B
Fintech âą Artificial Intelligence âą B2B
SPD Technology is a global software product development company that delivers custom digital platforms, cloud and DevOps, AI/ML, and fintech/payment solutions. They specialize in application modernization, data analytics and engineering, system integration and APIs, security and quality engineering, and mobile/web UX/UI development. SPD works as a B2B partner for enterprise and growth-stage clients (notable customers cited include PitchBook and Poynt), focusing on building payment systems, billing and fraud-detection software, data platforms, and AI-enabled products for industries such as fintech, insurance, healthcare, and e-commerce.
âą Drive custom Machine Learning Accelerator (ASIC) technology for large-scale AI applications and global cloud infrastructure âą Evaluate complex digital designs focused on ML compute architecture and integration within AI/ML-driven systems âą Own cross-functional workstreams for end-to-end hardware-software integration and validation âą Bridge specification, design, verification, compiler, and performance teams across the ML compute IP ecosystem âą Review chip specifications and designs âą Develop integration plans with software and system partners and coordinate hardware/software delivery âą Lead bringup of ML compute features and integrate and validate complex hardware/software designs, including third-party IPs âą Develop validation firmware to verify hardware functionality âą Execute hardware-software co-simulation using RTL, emulation, and FPGA environments âą Use architectural simulators and performance models to correlate results âą Design validation tests and microbenchmarks to verify IP functionality and performance âą Author test plans with Design, Design Verification, Firmware, and Architecture teams âą Lead debugging with Design, DV, Software, and Architecture teams âą Root-cause functional failures and performance issues throughout the product development cycle âą Improve validation coverage and sign-off processes for tapeout and production deployment
âą Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, a related technical field, or equivalent practical experience âą 5 years of experience in two of the following: computer architecture, embedded firmware, ASIC design or verification, or integration and enablement of first/third party IPs âą Experience in hardware/software integration and validation âą Experience with register-transfer level (RTL) development, design verification, and evaluation âą Master's degree or PhD in Electrical Engineering, Computer Engineering or Computer Science, with an emphasis on computer architecture (bonus) âą 4 years of experience with C++/Python software design principles (bonus) âą Experience integrating complex hardware/software systems in accelerators (bonus) âą Experience developing firmware for embedded systems or accelerators (bonus) âą Experience debugging firmware using simulation tools (bonus) âą Knowledge of real-time operating system (RTOS) internals (bonus)
âą Fully remote work around the globe âą Hybrid work model from office hubs âą Flexible working schedule âą Stable workload and stable income âą Performance reviews and career path âą Mentorship program âą Personal development plan âą Individual learnings through the corporate library âą Public speaking support âą Company-wide tech and cultural events âą Participation in meaningful CSR initiatives âą Supportive and flexible work environment âą Collaboration, open communication and mutual respect
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