Machine Learning Engineer - Fleet Intelligence

Job description

About Sibros

Sibros helps the world MOVE BETTER with the connected vehicle management platform that's purpose-built for the future of mobility, now. The automotive industry is undergoing seismic change with the shift towards cloud-connected, autonomous, shared, and electrified vehicle production. Join us on a journey where your talents will shape breakthrough digital innovations in luxury cars, commercial trucks, buses, performance bikes, and all other machines that can move, for years to come. Our award-winning, unified embedded firmware and cloud solution gives automakers everything needed to deliver new connected services, while improving vehicle safety and functionality with intelligent over-the-air updates and deep data analytics. Sibros is backed by top-flight investors including Google and Qualcomm and trusted by an exploding list of disruptive automotive brands, old and new. There has never been a better time to jump into a new era of massive industry transformation than now, with one of the fastest-growing companies in this space.

About the Role

Sibros’ fleet intelligence is one of the core products that offers OTA (over-the-air) data collection to a fleet of vehicles and provides AI powered insights into fleet data analytics. This game changing product will bring automobile manufacturers the ability to access realtime data on millions scale fleets and take actions efficiently on advanced insights Sibros provides.

We are looking for a highly capable machine learning engineer to build and optimize our machine learning systems. You will be evaluating cloud native, SaaS, open source machine learning framework, performing statistical analysis to resolve data set problems, and enhancing the accuracy of our AI software's predictive automation capabilities.

To ensure success as a machine learning engineer, you should demonstrate solid data science knowledge and experience in a related ML role. A first-class machine learning engineer will be someone whose expertise translates into the enhanced performance of predictive automation software.

Your responsibilities include, but are not limited to:

  • Collaborate with product owners and engineering teams to determine and refine machine learning objectives.
  • Designing machine learning systems and self-running artificial intelligence (AI) software to automate predictive models.
  • Transforming data science prototypes and applying appropriate ML algorithms and tools.
  • Ensuring that algorithms generate accurate user recommendations and predictions.
  • Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.
  • Developing ML algorithms to analyze huge volumes of historical data to make predictions.
  • Running tests, performing statistical analysis, and interpreting test results.
  • Documenting machine learning processes.
  • Keeping abreast of developments in machine learning.

Minimum Qualifications

  • Advanced proficiency with Python, Java, and Golang code writing.
  • Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture.
  • In-depth knowledge of mathematics, statistics, and algorithms.
  • Superb analytical and problem-solving abilities.
  • Great communication and collaboration skills.
  • Excellent time management and organizational abilities.

Preferred Qualifications

  • Strong experience in writing software in production
  • Experience in designing and implementing ML/AI products on a large scale.
  • Experience in the public cloud and cloud-native technologies. E.g. AWS, GCP, Azure.
  • Master’s degree in computational linguistics, data analytics, or similar will be advantageous.
  • At least three years' experience as a machine learning engineer.

Equal Employment Opportunity

Sibros is committed to a policy of equal employment opportunity. We recruit, employ, train, compensate, and promote without regard to race, color, age, sex, ancestry, marital status, religion, national origin, disability, sexual orientation, veteran status, present or past history of mental disability, genetic information or any other classification protected by state or federal law.

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