Senior Software Engineer, Machine Learning Inference

Summary Description: 

Syntiant Corp., a leader in the high-growth AI software and semiconductor solutions space, has entered into an agreement to acquire a large, multi-national sensor business with global revenues in excess of $250 million per year, and is looking for an experienced and talented Senior Software Engineer of Machine Learning Inference to take on a critical role with expansive responsibilities and play a leading role in enhancing the Machine Learning function in a growing organization.

The Senior Software Engineer of Machine Learning Inference will be responsible for developing the core building blocks that power computer vision, speech, and other application-specific APIs. Our approach to machine learning emphasizes computational and numerical efficiency, achieving orders-of-magnitude improvements over the state-of-the-art. These efficiency gains stem from fundamental ML innovations, built within a generalized production framework that enables rapid deployment of real-world products.

Specific Duties and Responsibilities:

• Develop, optimize, and maintain high-performance C/C++ software for CPUs, DSPs, NPUs, and GPUs.
• Profile and optimize inference code for power, latency, and throughput on edge devices.
• Develop tools to benchmark and profile AI models on resource-constrained platforms.
• Research and implement state-of-the-art ML models with a focus on computational efficiency.
• Debug and analyze performance bottlenecks in large-scale deployable software.
• Collaborate with hardware architects to co-optimize software and hardware solutions.

Requirements

Qualifications, Education, and Experience Required:

• BS in Computer Science/Engineering or related field (MS or PhD preferred).
• 5+ years of industry experience in software development and optimization.
• Strong C/C++ programming skills with a focus on performance optimization.
• Experience programming numerical algorithms in ML or related fields.
• Strong understanding of linear algebra and numerical optimization.
• Hands-on experience optimizing code for edge devices, including CPUs, DSPs, NPUs, GPUs, or other specialized processors.
• Deep understanding of low-level computing, memory hierarchies, and parallel processing techniques.
• Experience with assembly-level optimizations, vectorization (SIMD), and low-level debugging.
• Familiarity with profiling tools such as perf, gprof, Valgrind, Intel VTune, NVIDIA Nsight, etc.
• Experience with machine learning inference frameworks (TensorFlow Lite, ONNX Runtime, TVM, etc.).
• Knowledge of AI model compression, quantization, and pruning techniques.
• Knowledge of compiler optimizations and JIT compilation techniques.
• Experience working in large, complex codebases with version control tools like Git.

Benefits

About Syntiant:

Founded in 2017 and headquartered in Irvine, Calif., Syntiant Corp. is a leader in delivering hardware and software solutions for edge AI deployment. The company’s purpose-built silicon and hardware-agnostic models are being deployed globally to power edge AI speech, audio, sensor and vision applications across a wide range of consumer and industrial use cases, from earbuds to automobiles. Syntiant’s advanced chip solutions merge deep learning with semiconductor design to produce ultra-low-power, high performance, deep neural network processors. Syntiant also provides compute-efficient software solutions with proprietary model architectures that enable world-leading inference speed and minimized memory footprint across a broad range of processors. The company is backed by several of the world’s leading strategic and financial investors including Intel Capital, Microsoft’s M12, Applied Ventures, Bosch Ventures, the Amazon Alexa Fund, and Atlantic Bridge Capital. More information on the company can be found by visiting www.syntiant.com.

One element in our total compensation package is base pay.  The starting base pay for this role is targeted to be between $180,000 - $230,000. Individual compensation decisions are based on a number of factors, including but not limited to previous experience and skills acquired prior to joining Syntiant, cost of living in the assigned work location, assigned schedule, and salaries of similarly situated peers at the company. It is to be expected that candidates will come to us with different sets of skills and experiences and therefore will be paid at different points in the stated range. We recognize that the person(s) we select for hire may be less experienced or more experienced than the role as posted; if this is the case, any updates to available salary ranges will be communicated with candidates during the recruitment process.