Hi,
PFB the Job Description;
Required:
BS or MS in Computer Science Computer Engineering or similar field At least 4 years of
experience in developing and deploying end-to-end AI/ML solutions in production environment
with good working knowledge of the Linux operating system Experience with TensorRT or
OpenVINO is a plus and deep expertise with Kubernetes and Docker containers
Design, implement, and optimize algorithms to run on edge devices
Design and implement the split/interaction between edge and cloud algorithms
Leverage the Edge compute available to run a variety of offline algorithms spawning multiple
use cases (i.e., complex video analytics tasks)
Ability to adapt and ramp up on Android and Linux
Implementation of end-to-end ML Ops/analytics solutions as per the industry standard process
Explore, devise, and implement ML algorithm stack
Experiment, prototype and finalize specific solution with the best business metrics
Design and implement architecture/tech stack for data integration, data flow and data storage
for ML solutions
Deliver production quality, modular and reproducible code
Create data visualizations to visualize raw data and analytics insights to demonstrate efficacy
of the solution
Skills:
Exposure to reinforcement learning, supervised and unsupervised algorithms, various
architectures of neural networks, time series forecasting, deep learning networks
Deep expertise in any specific application of ML and DL
Prior experience in building and deploying ML pipelines from data ingestion, preparation to
deploying models in production
An understanding of various databases relational, NoSQL with prior experience in any DB
Exposure to ML and DL frameworks like TensorFlow, PyTorch, Caffe, etc
Familiarity with ML testing and data validation frameworks
Familiarity with IoT communication protocols like MQTT
Interested Candidates can apply with updated cv on as****s@an***e.co.in
Regards,
Ashis
Keyskills: Tensorflow Machine Learning artificial intelligence pytorch edge AI mlops DNN Edge Artificial intelligence deepops ML algorithm stack TensorRT reinforcement learning cloud2edge deep learning Jetson AI Docker OpenVINO Caffe ML Ops/analytics edge2cloud Kubernetes