🎁 Before you apply, rehearse this interview. Create your free WorkMundi account and get an Interview Training on HelpsYouSpeak — no cost, no card. I want my training →
We are seeking a talented engineer to implement and optimize machine learning, computer vision, and numeric libraries for target hardware architecture, including CPUs, GPUs, DSPs, and other accelerators. Your expertise will be instrumental in enabling efficient and high-performance execution of algorithms on these hardware platforms. Key Responsibilities: Implement and optimize machine learning, computer vision, and numeric libraries for target hardware architectures, including CPUs, GPUs, DSPs, and other accelerators. Work closely with software and hardware engineers to ensure optimal performance on target platforms. Implement low-level optimizations, including algorithmic modifications, parallelization, vectorization, and memory access optimizations, to fully leverage the capabilities of the target hardware architectures. Work with customers to understand their requirements and implement libraries to meet their needs. Develop performance benchmarks and conduct performance analysis to ensure the optimized libraries meet the required performance targets. Stay current with the latest advancements in machine learning, computer vision, and high-performance computing. Qualifications: BTech/BE/MTech/ME/MS/PhD degree in CSE/IT/ECE > 4 years of experience working in Algorithm Development, Porting, Optimization & Testing Proficient in programming languages such as C/C++, CUDA, OpenCL, or other relevant languages for hardware optimization. Hands-on experience with hardware architectures, including CPUs, GPUs, DSPs, and accelerators, and familiarity with their programming models and optimization techniques. Knowledge of parallel computing, SIMD instructions, memory hierarchies, and cache optimization techniques. Experience with performance analysis tools and methodologies for profiling and optimization. Knowledge of deep learning frameworks and techniques is good to have Strong problem-solving skills and ability to work independently or within a team. Algorithm Engineer (CPU/GPU/DSP/FPGA) Job Summary We are looking for an Algorithm Engineer with experience in optimizing software for CPUs, GPUs, DSPs, and FPGAs. The role involves developing high-performance algorithms for machine learning, computer vision, and numerical applications. Key Responsibilities Develop and optimize algorithms for CPUs, GPUs, DSPs, and FPGAs. Work on machine learning, computer vision, and numerical libraries. Improve application performance through optimization techniques. Work closely with software and hardware teams. Analyze performance and fix bottlenecks. Support customer requirements and deliver optimized solutions. Required Skills B.E./B.Tech./M.E./M.Tech./MS in Computer Science, Electronics, ECE, or related field. 4+ years of experience in algorithm development or software optimization. Strong programming skills in C/C++. Experience with CUDA, OpenCL, or similar parallel programming technologies. Experience working with CPUs, GPUs, DSPs, or FPGAs. Hands-on experience with FPGA development using VHDL, Verilog, HLS, Xilinx Vivado/Vitis, Intel Quartus, or similar tools. Good understanding of performance optimization, parallel computing, and memory optimization. Good problem-solving and debugging skills. Good to Have Experience with TensorFlow, PyTorch, or other AI/ML frameworks. Knowledge of LLVM, MLIR, or TVM. Experience in embedded systems or AI acceleration. This version is much simpler, recruiter-friendly, and broad enough to attract candidates with either Algorithm Optimization or FPGA acceleration experience. .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.