Machine Learning Engineer - Hardware-Accelerated ML & Compiler

Nutanix; New York (NY); On-site; USD 141,000 - 211,000; Full time

Job summary

Qualcomm Technologies, Inc. is seeking a Machine Learning Engineer to create and implement ML techniques, frameworks, and tools for efficient discovery and utilization of state-of-the-art ML solutions across devices like mobile, edge, auto, and IoT.

You will collaborate with cross-functional teams to enhance ML hardware and software, optimizing ML models for inference/training on dedicated hardware and contributing to product roadmaps.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field.
• Master's degree in Computer Science, Engineering, Information Systems, or related field (preferred).
• 1+ year in ML frameworks (TensorFlow, Caffe, Caffe2, PyTorch, Keras).
• 1+ year embedded systems development & optimization for ML domains (e.g., NLP, multimedia).
• 1+ year programming in Python, R, C, or C++.
• 1+ year statistics & probability (Bayes).
• 1+ year experience in a large matrixed organization.
• 6+ months experience with low-level OS-HW interactions (Linux, Android, QNX).

Responsibilities

• Applies ML knowledge to extend training or runtime frameworks or model efficiency software tools.
• Assists in modeling, architecture, and development of ML hardware for inference or training solutions.
• Develops optimized software to enable AI models on hardware (kernels, compilers, model tools).
• Helps develop ML techniques into products/AI solutions for customers.
• Develops/adapts prototypes of ML algorithms, models, or frameworks aligned with product roadmap.

Skills

Machine learning frameworks

Embedded systems

Programming languages (Python, R, C, C

Statistics & probability

Large matrixed organizations

OS-HW interaction (Linux/Android/QNX)

Education

B.S. in Computer Science/Engineering/IS

M.S. in Computer Science/Engineering/IS (preferred)

Job description

Qualcomm Technologies, Inc. is seeking a Machine Learning Engineer to create and implement ML techniques, frameworks, and tools for efficient discovery and utilization of state-of-the-art ML solutions across devices like mobile, edge, auto, and IoT.

You will collaborate with cross-functional teams to enhance ML hardware and software, optimizing ML models for inference/training on dedicated hardware and contributing to product roadmaps.