Job Location: Chennai
Position Overview
As a computer vision deep learning engineer, you will be responsible for the development of state of the art solutions
enabling the next generation of Automated Driving Assistance Systems. Examples of such solutions include: Deep learning
based semantic segmentation, object detection, height & depth estimation, lane detection, park slot detection, object
classification & scene understanding, motion segmentation and fusion of multiple sensors. You will be expected to remain
abreast of technological developments support Valeo, DVS in maintaining and enforcing its position as world leader in the
field of automotive vision applications.
Responsibilities
Research, develop, benchmark, and document state of the art deep learning solutions for autonomous driving &
parking perception applications.
Perform research into new technology, ideas, and approaches in the deep learning domain.
Support Intellectual Property activities and generate Invention Disclosure Memos to facilitate patent applications.
Contribute to design reviews across algorithm teams.
Come up with ideas for next generation algorithms and new business opportunities
Develop algorithms with a view to implementing Hardware Accelerators
Represent Valeo, DVS at various Industry Working Groups and at Conferences where directed
Support the design and implementation of in-company training sessions in your area of expertise
Develop and maintain relationships with university counterparts
Transforming data science prototypes and applying appropriate ML algorithms and tools
Identify and suggest / implement improvements within the current processes used in algorithm development
Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries
and frameworks
Developing ML algorithms to analyse huge volumes of historical data to make predictions
Running tests, performing statistical analysis, and interpreting test results
Required Skills /Experience
BE / B-Tech degree or ME / MS degree or PhD in Physics, Electronic Engineering, Software Engineering with
minimum 3 years’ experience in Deep Learning
Industry experience in applied research in the field of deep learning and computer vision
Exposure to state of the art technologies in Deep learning (e.g. GANs, LSTM, Bayesian Machine Learning,
Experience in Deep Learning in one of the following: object detection, segmentation, tracking, pose estimation,
action recognition, differentiable rendering
Expert in Python programming and good understanding of deep learning frameworks and workflow
Experience in working with large data sets and developing infrastructure pipelines
Strong fundamentals in 3D geometry
Strong knowledge of camera parameters and colour models,
High level of innovation and motivation
Extensive knowledge of ML frameworks, libraries, data structures, data modelling, and software architecture
In-depth knowledge of mathematics, statistics, and algorithms
Superb analytical and problem-solving abilities
Good communication and collaboration skills
Desired Attributes
Specialisation in Machine Learning preferred.
Applied Deep Learning work experience preferred.
Academic publications in relevant field
Experience with parallel programming in CUDA, or OpenCL
Algorithm development experience in robotics, ultrasonics, RADAR, LIDAR, camera systems, sensor fusion or
computer vision
Experience with PC-based simulation tools
Knowledge of UML design tools
Experience developing software for embedded platforms.
Experience with version control software
Experience developing algorithms for autonomous and/or real-time systems.
Experience with imaging or optics systems.
Automotive industry experience.
BE / B-Tech degree or ME / MS degree or PhD in Physics, Electronic Engineering, Software Engineering with
minimum 3 years’ experience in Deep Learning
Primary Location
: IN-TN-Chennai 7
Job
: Research and Development
Organization
: 12L Vision Systems
Schedule
: Full-time
Shift
: Day Job
Employee Status
: Regular
Job Type
: Regular
Job Posting
: 06/10/2022, 12:19:19 AM
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