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
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Research, develop, benchmark, and document state of the art deep learning solutions for autonomous driving &
parking perception applications.
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Perform research into new technology, ideas, and approaches in the deep learning domain.
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Support Intellectual Property activities and generate Invention Disclosure Memos to facilitate patent applications.
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Contribute to design reviews across algorithm teams.
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Come up with ideas for next generation algorithms and new business opportunities
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Develop algorithms with a view to implementing Hardware Accelerators
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Represent Valeo, DVS at various Industry Working Groups and at Conferences where directed
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Support the design and implementation of in-company training sessions in your area of expertise
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Develop and maintain relationships with university counterparts
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Transforming data science prototypes and applying appropriate ML algorithms and tools
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Identify and suggest / implement improvements within the current processes used in algorithm development
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Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries
and frameworks
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Developing ML algorithms to analyse huge volumes of historical data to make predictions
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Running tests, performing statistical analysis, and interpreting test results
Required Skills /Experience
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BE / B-Tech degree or ME / MS degree or PhD in Physics, Electronic Engineering, Software Engineering with
minimum 3 yearsโ experience in Deep Learning
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Industry experience in applied research in the field of deep learning and computer vision
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Exposure to state of the art technologies in Deep learning (e.g. GANs, LSTM, Bayesian Machine Learning,
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Experience in Deep Learning in one of the following: object detection, segmentation, tracking, pose estimation,
action recognition, differentiable rendering
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Expert in Python programming and good understanding of deep learning frameworks and workflow
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Experience in working with large data sets and developing infrastructure pipelines
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Strong fundamentals in 3D geometry
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Strong knowledge of camera parameters and colour models,
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High level of innovation and motivation
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Extensive knowledge of ML frameworks, libraries, data structures, data modelling, and software architecture
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In-depth knowledge of mathematics, statistics, and algorithms
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Superb analytical and problem-solving abilities
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Good communication and collaboration skills
Desired Attributes
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Specialisation in Machine Learning preferred.
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Applied Deep Learning work experience preferred.
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Academic publications in relevant field
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Experience with parallel programming in CUDA, or OpenCL
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Algorithm development experience in robotics, ultrasonics, RADAR, LIDAR, camera systems, sensor fusion or
computer vision
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Experience with PC-based simulation tools
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Knowledge of UML design tools
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Experience developing software for embedded platforms.
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Experience with version control software
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Experience developing algorithms for autonomous and/or real-time systems.
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Experience with imaging or optics systems.
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Automotive industry experience.
BE / B-Tech degree or ME / MS degree or PhD in Physics, Electronic Engineering, Software Engineering with
minimum 3 yearsโ 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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