KlearNow is pioneering “Logistics as a Service” (LaaS) by creating the industry’s first fully cloud-based digital network that can be used across the entire array of supply chain participants to simplify the transit of goods worldwide. KlearNow’s LaaS model/platform is powered by our proprietary artificial intelligence/machine learning (AI/ML) engine that automates the digitization of the many current siloed, manual, and paper-based processes – ultimately turning a mass of disconnected data into a structured and
KlearNow is operational and a certified Customs Business provider in US, Canada and UK with plans to grow in many more markets in near future. Be a part of a rapidly growing company where you will have the opportunity to extend our leadership position and fast-track innovation behind AI-powered intelligent supply chain solutions.
Over and above the core customs clearance solution, KlearNow is also providing consolidated freight visibility, data and document management and intra-port activity for efficient Drayage.
KlearNow has the flexibility of a small start up with the security of a well-funded organization with strong investors and advisors.
- Design and develop innovative AI solutions for challenging business problems.
- Discover data sources, get access to them, import them, clean them up, and make them “machine learning ready”.
- Build backend systems that interact with other microservices.
- Train and optimize machine learning models.
- Engineer machine intelligence systems and infrastructure for real-world production use at scale.
- Explore data features and manipulate data with SQL and scripts.
- Running machine learning tests and experiments
- Implementing appropriate ML algorithms
- Should be able to understand the problem statement and be able to justify the usage of AI/ML as a solution
- Be able to understand requirements and fine tune them to provide results for concrete problems
- Strong coding experience in Python and working with related libraries (NumPy/Pandas/matplotlib).
- Familiarity with machine learning frameworks (Keras/PyTorch/Tensorflow) and relevant libraries.
- Excellent knowledge and good practical skills in major ML algorithms as applied to Natural Language Processing and Computer Vision.
- Practical experience with deep learning projects is highly valued.
- Ability to improve the accuracy, runtime, scalability and reliability of machine intelligence systems.
- Strong in understanding underlying math, probability, statistics and algorithms.
- Passion for continuing to learn state-of-the-art techniques in ML/Data science.