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Technical Lead – Embedded Machine Intelligence

Summary

Salary
£Competitive
Team
Motors and Power Systems
Location
Malmesbury - United Kingdom

Description

Dyson offers a unique opportunity for a talented and experienced Lead Embedded Electronics Engineer in the Technical Research Team, within Dyson’s Research, Design and Development (RDD) department; based in Malmesbury, Wiltshire, U.K.

The Technical Lead role will be responsible for the design of a range of algorithms for deployment on embedded systems.  Main areas will include embedded image processing, machine vision and sensor fusion to augment machine vision systems.  The role sits within Technical Research, reporting to the Research Manager for Embedded Electronics & Software.

The Power Electronic & Electronic Systems Research team is responsible for the delivery of various Power Electronic and Embedded Electronic technologies to key company milestones and transferring the technologies to the development teams.  The work often involves shorter term projects targeting specific products, alongside longer term research projects to bring emerging technologies into future products.  It is typical to be involved in several projects running concurrently.



Accountabilities

  • Being the technical leader for embedded machine intelligence in the team covering embedded image processing, machine vision and sensor fusion to augment machine vision systems.
  • Working with the different sub teams within Technical Research, as well as NPI, other research groups and development teams to gain an in depth product understanding, while using your expert knowledge of the latest technologies to create innovative systems and solutions.
  • Striving to find and develop the best concept and demonstrate designs are robust and viable for use in product through detailed laboratory testing, prior to handover to the development teams.
  • Generation of suitable test specifications to ensure product reliability and robustness at key stages. This may include test environment development, including simulation, emulation and hardware/test equipment interactions.
  • Assisting in the personal development of the Embedded Machine Intelligence team and undertaking regular performance conversations with the team, as well as setting goals/objectives for team members.
  • Leading algorithm design review activities.
  • Working with other disciplines to solve complex system level problems.
  • Pulling together review packs which typically include concept specifications, requirements and specification documentation, risk registers, FMEAs and design guides for reviews.
  • Working with the project management team to ensure project plans are created, updated and deliverables are ready for each milestone review.
  • Driving the team to develop simulations where appropriate to optimize designs.
  • Managing technical risks in a project through FMEAs, reporting, and actively driving down risk with targeted tasks.
  • Researching into new and emerging technologies through visiting conferences, trade shows, meeting suppliers, reading papers and patents.

Skills

Education and experience:

·    BEng/MEng degree in Electronic Engineering, Computer Science, or other relevant discipline, or a demonstrable level of industrial experience in a relevant industry.

·       The team is a research team and candidates should be able to demonstrate an ability to innovate and research (e.g. through patent publications, papers, developing new technologies etc).

Technical knowledge:

Applicants should ideally have experience in the following areas:

·       Vision and optical sensor systems

o   An understanding of vision systems and image processing and machine vision is essential.

o   Knowledge of multispectral or hyperspectral imaging desirable.

o   Knowledge of a wide range of sensors that can be used in a variety of projects and not necessarily in existing categories you would expect from Dyson is desirable.

·       Hardware design:

o   Excellent general knowledge of microcontrollers, preferably including ARM Cortex M series.

o   Knowledge of a wide range of serial interfaces (e.g. MIPI, I2C, SPI, UART, USB, I2S).

o   Experience of application processors for embedded systems.

o   FPGA VHDL/Verilog design.

·       Software:

o   Knowledge of common software design methodologies and embedded software development in assembler and C/C++.

o   Familiar with the requirements for ‘hard real time’ embedded software applications and demonstrable experience of working within real time constraints.

o   Ability to derive software requirements from product level requirements and derive own requirements when limited information is available.

o   Expert in digital signal processing experience and ability to optimise algorithms on embedded hardware.

o   Experience of programming on Linux or Android operating systems running on application level processors.

o   Knowledge of a wide range of functions and algorithms commonly used image processing and machine vision and general sensor systems, including machine learning approaches e.g. SVM, CNNs etc. 

o   Knowledge of openCV.

o   Knowledge of tensorflow and other tools commonly used in machine learning (such as Keras, Caffe etc).

·       Design Tools:

o   Ability to Matlab, Python or other suitable tools for algorithms development and test.

·       Design Techniques:

o   Circuit simulation and design tolerance analysis.

o   Good quality engineering process understanding and appreciation.

o   Robust design including FMEA techniques.

o   Familiar with creating requirement documents.

·       Lab experience

o   Experience of working in a laboratory environment.

    • Use of lab equipment to set up experiments and to take precise measurements
    • Experience of writing risk assessments for lab based testing.

Essential Management skills:

·       A candidate should be able to demonstrate previous people manage experience, including running 1:1 meetings with direct reports and setting objectives.

·       Experience of developing individuals in a team through personal development plans and developing training plans for teams.

·       Project management experience – ability to work with teams to generate task lists and timelines to build project plans and manage risk in projects.


Benefits

27 days holiday plus eight statutory bank holidays

Pension scheme

Performance related bonus

Life assurance

Sport centre

Free on-site parking

Subsidised café and restaurants

Discounts on Dyson machines