Senior Software Engineer, Machine Learning


Company Description:

Who we are: 

Motive builds technology to improve the safety, productivity, and profitability of businesses that power the physical economy. Motive combines IoT hardware with AI-powered applications to connect and automate physical operations. Motive is one of the fastest-growing software companies in the world, serving more than 120,000 businesses, across a wide range of industries including trucking and logistics, construction, oil and gas, food and beverage, field service, agriculture, passenger transit, and delivery.

Motive is built on four foundational attributes; Own It, Less but Better, Build Trust, and Unlock Potential. This has taken our company to great heights, including being recognized by Fortune for Best Workplaces, Forbes Best Startup Employers, and Comparably for our Best Global Culture, Sales Team, Leadership Team, Career Growth, and CEO for Diversity. We’re proud to receive an employee net promoter score of 63 (according to Comparably) which places Motive in the top 5% of companies with 4,000 employees or more. 

Today, our team is made up of more than 3,000 employees, located across the world, providing support to a wide range of customers. While most of our employees are remote, many have the opportunity to work on-site at any of our 8 global office locations. Visit our careers website to learn more about opportunities at Motive. 

About the role: 

As a Software Engineer – Machine Learning, you will be a part of a passionate team whose mission is to bring intelligence to the world’s trucks. The team is focused on building technology to understand driving behavior, identify risk factors, and intelligently suggest coachable events that not only improve the fleet safety and potentially save millions of dollars but also contribute to making the roads safer. You will have a unique opportunity to work with a high-caliber and fast-paced team which consists of experienced researchers and engineers in Computer Vision, Machine Learning, Deep Learning, and Robotics with a track record of previous products and top-tier publications. 

You will play a critical role in building and improving a technology that will be used by millions of trucks. In this role, you will design and implement complex machine-learning systems. You will have the opportunity to build and/or improve ML/computer vision systems. Identify where models and algorithms are failing, debug issues, propose solutions, implement, and deploy them on millions of trucks. You will also get exposure to large-scale ML infra and scaling that facilitates large amounts of data to train, test, and validate computer vision systems.

What You’ll Do: 

  • Evaluate and improve the performance of existing models and algorithms already in production
  • Prototype and implement ML modules for complex AI features
  • Build and optimize CV/ML algorithms for real-time performance so they can run on our embedded platform, i.e., the next-gen AI dashcam
  • Write proficient Python and C++ code to build and improve CV algorithms, ML services, training, model compression, and porting pipelines
  • Collaborate with cross-functional teams such as Embedded, Backend, Frontend, Hardware, QA, and the broader AI team to ensure the development of robust and sustainable AI systems
  • Build automated deployment, validation, and active learning pipelines.

What We’re Looking For: 

  • Bachelor’s Degree in Computer Science, Electrical Engineering, or related field. A Master’s degree is a plus. 
  • 5+ years of machine learning and/or data science experience
  • Solid mathematical foundation in Deep Learning, Machine Learning, and optimization approaches.
  • Strong experience in Python or C++
  • Experience in the following tools and technologies is a plus. AWS (SageMaker, Lambda, EC2, S3, RDS), CI/CD, Terraform, Docker, and Kubernetes.

APPLY HERE


Published On: July 26, 2023 16:01

DETAILS

Salary: Unknown PKR

Experience: 5+ years

Job Type: Full Time

Location: Remote

Published: July 26, 2023

Update: July 26, 2023

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