Algorithms & optimization Engineer

We are looking

for a talented engineer to implement and optimize machine learning, computer

vision, and numeric libraries for target hardware architectures, 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.

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.

Requirements

Education:

BTech/BE/MTech/ME/MS/PhD

in CSE/IT/ECE.

Technical Skills (Must haves):

• 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.

Need to have (Can be bridged):

• More than 4 years of experience in Algorithm

Development, Porting, Optimization & Testing.

• Strong problem-solving skills and ability to work

independently or within a team.

Good to have (Not essential):

Knowledge of

deep learning frameworks and techniques.

Preferred Qualifications (Optional):

Hands-on

experience optimizing algorithms and libraries for heterogeneous hardware

platforms and high-performance computing environments.