Deep Learning Engineer (On-site)
Location – Bangalore, India. Employment Type – Full time.
About us:
Flux Auto builds autonomous vehicle technology for commercial and industrial
applications.
Flux Auto was founded in 2017 with the goal of democratizing autonomous vehicle
technology and bringing its benefits to vehicles – new and old – around the world. We
develop various hardware and software technologies to make vehicles move and
operate autonomously. Every day our engineers are working to solve new and unique
challenges for our clients in India and North America.
We are a multidisciplinary team solving some of the most challenging problems in
autonomous technology and robotics. Join us in our journey to democratize autonomous
mobility!
Experience required: 1 – 3 years.
About the role:
Looking for an engineer to apply Deep Learning algorithms to implement and improve
perception algorithms related to Autonomous vehicles. The position requires you to work on the full life-cycle of Deep learning development including data collection, feature engineering, model training, and testing. One will have the opportunity to implement a state-of-the-art Deep learning algorithm and apply it to real end-to-end production. You will be working with the team and team lead on challenging Deep Learning projects to deliver product quality improvements.
Responsibilities:
users.
future behavior of other road users in real-time.
Requirements:
Good to Have:
GAN, etc.)
Benefits:
Equal Opportunity Employer:
Flux Auto’s employment decisions are made without regard to race, color, religion,
national origin, gender, sexual orientation, age, gender identity, genetic factors,
military/veteran status or other characteristics protected by law.
Vaccination Requirements:
Flux Auto is implementing new requirements for employees to be fully vaccinated from
COVID-19.
For further information,
Contact us on www.fluxauto.xyz or
Phone number: +91 85508 55800
Apply Now!
Job Types: Full-time, Regular / Permanent
Salary: ₹300,000.00 – ₹900,000.00 per year
Benefits:
Schedule:
Supplemental Pay:
Ability to commute/relocate:
Experience:
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