Job Description

:

Company: Qualcomm India Private Limited

Job Area: Engineering Group, Engineering Group
Systems Engineering

General Summary:

General Summary:

We at Qualcomm MIST are a passionate team of engineers who want to change the world of wearables by coming up with consumer grade healthcare services which would be adopted by masses. The core MIST team consists of researchers and engineers who have successfully deployed the first commercial ultrasound fingerprint sensors widely used in millions of phones worldwide. The Qualcomm MIST team is rapidly expanding and seeking innovators who will revolutionize the healthcare industry. We are hiring at our Hyderabad, India location.

The MIST team has the perks of being a start-up working almost autonomously under a bigger brand like Qualcomm. We are a world-class engineering organization developing state-of-the-art machine learning, signal processing and deep learning solutions to deliver ultra-optimized, power-efficient software and hardware to enable at-home mass produced health monitoring systems.

To scale and strengthen our offering in this domain, Qualcomm MIST team in Hyderabad, India is rapidly expanding and seeking candidates to investigate and develop the fundamental signal processing and machine learning algorithms to improve the perception of the data we collect.

Overview

(Job Function/General Responsibilities)

Role responsibility can include both, applied and fundamental research in the field of machine learning with development focus in one or many of the following areas:

• Conducts fundamental machine learning research to create new models or new training methods in various technology areas, e.g. deep generative models (VAE, Normalizing-Flow, ARM, etc), Bayesian deep learning, equivariant CNNs, adversarial learning, active learning, Bayesian optimizations, unsupervised learning, and ML combinatorial optimization using tools like graph neural networks, learned message-passing heuristics, and reinforcement learning.

• Performs advanced platform research to enable new machine learning compute paradigms, e.g., compute in memory, on-device learning/training, edge-cloud distributed/federated learning, quantum machine learning, causal and language-based reasoning.

• Creates new machine learning models for advanced use cases that achieve state-of-the-art performance and beyond.

• Design, develop & test software for machine learning frameworks that optimize models to run efficiently on wearables.

• Design, implement and train DL/RL algorithms in high-level languages/frameworks (PyTorch and TensorFlow).

• This position requires a background in photoacoustics, ultrasonics and audio signal processing, biosensing, and general knowledge of human anatomy and physiology.

Overview

(Critical \xe2\x80\x9cMust Have\xe2\x80\x9d skills/experience for role)

• Strong signal processing fundamentals and knowledge of voice and signal processing techniques including adaptive filters, multi-mic beamforming, Fourier/Z transforms, equalizers & linear algebra.
• Experience using modern deep learning toolboxes (e.g., Py Torch, TensorFlow), machine learning pipelines, model evaluation and data visualization.
• 5+ years of industry experience is required.
• Good understanding and strong knowledge in algorithms and statistics
• Good understanding and experience in math function optimization
• Be able to stay on top of state-of-the-art approaches.
• Experience with data generation/augmentation for deep neural networks using Matlab and python scripting.
• Familiarity with training neural networks using Py torch, Caffe, TensorFlow and ONNX
• Familiarity with operations and concepts of CNN, FC, RNN/LSTM/GRUs,
• Excellent verbal and written communication and presentation skills
• Committed team player and ability to take ownership of their work
• Knowledge of fixed-point programing in C/Matlab
• Expertise in multi-mic array processing, beamforming, adaptive beamforming, direction of arrival estimation etc
• Expertise in digital signal processing techniques such as signal modeling, spectrum analysis and estimation, statistical signal processing, adaptive filter theory

Overview

(Preferred skills/experience for role)

At least one of the points below is a must

• Prior experience of working with AWS or Azure
• Prior experience of working with Bigdata/Distributed computing in real time and offline
• Prior experience of descriptor training, matching neural networks training, image retrieval/search task, segmentation
• Experience of delivering reliable ML models to the production
• Experience in software development, incl. testing and debugging mobile platforms, wearables or other embedded systems.
• Excellent C++ and object-oriented programming

Education

Required: Master with 5 years of industry experience or PhD with 2 years of industry experience

Computer Science, Computer Engineering, Electrical Engineering, Applied Math

Minimum Qualifications: \xe2\x80\xa2 Bachelor\'s degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
OR
Master\'s degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Systems Engineering or related work experience.
OR
PhD in Engineering, Information Systems, Computer Science, or related field.

Applicants: If you need an accommodation, during the application/hiring process, you may request an accommodation by sending email to

Although this role has some expected minor physical activity, this should not deter otherwise qualified applicants from applying. If you are an individual with a physical or mental disability and need an accommodation during the application/hiring process, please call Qualcomm\xe2\x80\x99s toll-free number found for assistance. Qualcomm will provide reasonable accommodations, upon request, to support individuals with disabilities as part of our ongoing efforts to create an accessible workplace.

Qualcomm is an equal opportunity employer and supports workforce diversity.

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.

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