Computer Vision/Deep Learning Engineer

Algoface; Carefree (AZ); On-site; USD 90,000 - 120,000; Full time

Job summary

Algoface is seeking a Computer Vision/Deep Learning Engineer in Carefree, Arizona. You will focus on building deep learning computer vision applications related to face detection, recognition, and soft biometrics. Candidates should have a minimum of 3 years in industrial applications and strong skills in TensorFlow, Keras, and PyTorch. The role requires excellent English communication skills and expertise in optimizing deep learning models. Join us to drive innovations in computer vision technology.

Qualifications

• At least 3 years of experience in industrial computer vision and deep learning applications.
• Very good English writing and verbal communication skills.
• Strong coding skills in TensorFlow, Keras, and PyTorch.

Responsibilities

• Build scalable applications for face detection, recognition, and soft biometrics.
• Optimize deep learning models to save time and energy.
• Manage machine learning model lifecycles.

Skills

English writing and verbal communication

Data processing

Data cleaning

Data analysis

Data augmentation

TensorFlow

Keras

PyTorch

Optimizing deep learning models

Building cloud solutions

Linux environments

Machine learning models lifecycle management

Face Detection

Face Recognition

Face Analysis

Deploying models on the edge

Job description

Computer Vision/Deep Learning Engineer

We are looking for Computer Vision/Deep Learning to work on building deep learning computer vision scalable applications related to face detection, recognition, and soft biometrics.

Ideally, you have already completed at least 3 years of experience in industrial computer vision and deep learning applications with skills in:

1. Very good English writing and verbal communication skills.
2. Data processing, cleaning, analysis and augmentation.
3. Strong coding skills in Tensorflow, Keras , Pytorch to code both prototypes and production level systems.
4. Experience in optimizing deep learning models to save time and energy and memory requirements in both training and inference phases.
5. Ability to build complete solutions that run on the cloud or an independent server on Linux environments.
6. Machine learning models lifecycle management.
7. It will be a big plus if you have experience in Face Detection, Recognition and Analysis.
8. + 3 years industrial experience.
9. Big bonus if you have experience in deploying deep learning models on the edge.