Texas Instruments Mixed Signal Processing AI Research Engineer 

United States, Texas, Dallas 

664212521

Signal Processing and AI Research Engineerto join TI's central R&D organization, Kilby Labs. You will apply your analog and digital signal processing and AI expertise to innovate on intelligent time series data processing approaches that addresschallenges and opportunities in emerging industrial, medical, and consumer applications. You will architect, design, simulate and prototype system solutions utilizing the new data processing approaches and work with technologists in Kilby and across TI to define highly differentiated future IC products that bring new values to our customers and make broad impact.

About the organization:

Kilby Labs, TI's central R&D organization, is a global organization grouped by a variety of research engineers from multiple technology disciplines to deliver semiconductor devices and solutions for future large volume products in a fast moving pace.

Responsibilities include:

• : Define, simulate, design and develop a system level solution in various application areas (industrial, medical, automotive and consumer) with highly differentiated features: performance, power, cost, ease of use, etc.
• Time Series Signal Processing
  : Define, design and develop highly optimized signal processing and AI algorithms to extract information from a sensing signal path, or create the desired effect in an actuation signal path, or a combined active sensing approach that involves both actuation and sensing. Be able to infer or classify unique information from time-domain, frequency domain signal pre-processing and neural network models as well as post-processing in a very resource constraint device environment with unique optimization methods.
• Hardware Design and Prototyping
  : Broad analog and digital high-speed high-precision HW digital and analog design and prototypes. Be able to interact with IC development team for complete IC level signal path design and applications.
• Simulation & Verification
  : Quickly provide comprehensive system level simulations to validate the viability of a given solution, analyze system performance requirements and perform system tradeoff analysis.
• Customer Interactions
  : Work with multiple business units across the company to support productization of the systems. Work with early stage driver customers and/or 3^rd
• Emerging Technologies
  : Continuously stay up to date with competitive landscape for performance benchmark and find new applications/opportunities in the embedded analytics space using existing TI products or define future products.
• Execution
  : Aggressive on-time delivery of the project milestones with clear understanding of project plan, focus on key priorities and work-through various constraints. Highlight potential risks at the early stage and come up with prompt mitigation plans.

Minimum requirements:

• Doctoral degree in Electrical Engineering, Electrical and Computer Engineering or related field
• Cumulative 3.0/4.0 GPA or higher

Preferred qualifications:

• Strong track record and expertise in mixed signal processing algorithms, devices, use of IC products and AI model development.
• Proficient with Python/Matlab/Simulink for system simulation. Simulation shall include sensor model, analog/digital signal chain and algorithm for complete system analysis and solution development.
• Comfortable with debugging system in lab environment using oscilloscope, spectrum analyzer, function generator, power supply and other lab equipment.
• Experience in system prototypes, optimization and application demonstration. Proficiency in analog and basic digital IC design for mixed signal circuits is a plus.
• Experience with programming languages such as C/C++, real-time operating system, embedded software, and MCU development environments is a plus.
• Ability to work in teams and collaborate effectively with people with different functions.
• Understanding of the latest techniques in deep neural networks, Large Language models, and scaling techniques. Experience in developing or using deep learning frameworks (e.g. Tensorflow, Keras, Caffe, PyTorch, ONNX, etc.)
• Knowledge in one or more systems that involve sensors in current/motion/acoustic, optical, ultrasound, mmWave and other sensing modalities.
• Has engaged with sensing systems used in industrial, medical, automotive and other consumer applications.