EDGE Machine Learning Engineer

EDGE Machine Learning Engineer



We are taking part in the development of a healthcare startup. The main purpose is to monitor patients in the hospital, and the main feature is an application for 24-hour video surveillance. Now we're developing an AI-driven system aimed at preventing patient falls from beds and reducing the occurrence of wounds or injuries.

The client is one of the world’s largest manufacturers of appliances and electronics.

Poland, Ukraine (Lviv, Cherkasy), Remote
technical details
Stack: TypeScript/JavaScript, Node.js, React, MySQL, Kubernetes, Docker, Elastic Kubernetes Service, Terraform, Helm, AWS, Twilio Video SDK. For AI: JS, OpenCV, Tensorflow, Tensorflow JS, PoseNet, Coco SSD. Architecture: Simple monolith application. Possible migration to Service-oriented architecture.
technical details
Stack: TypeScript/JavaScript, Node.js, React, MySQL, Kubernetes, Docker, Elastic Kubernetes Service, Terraform, Helm, AWS, Twilio Video SDK. For AI: JS, OpenCV, Tensorflow, Tensorflow JS, PoseNet, Coco SSD. Architecture: Simple monolith application. Possible migration to Service-oriented architecture.
job highlights
  • The application is in production
  • Development practices on the project include Code review, Build-in quality, Unit-testing and integration testing, End-to-end automated testing, CI, Release on demand
  • Working in a distributed multinational team in a different time zone. The approximate work schedule is from 11:00 AM to 7:00 PM CEST
  • Staffing cooperation format
  • Model Training: Train and fine-tune deep learning models using diverse datasets, including labeled video sequences, to achieve high accuracy in patient position detection and issue classification. That includes identification of anomalies and potential issues related to patient positioning, such as incorrect posture, movement constraints, or equipment malfunctions
  • Data Processing: Preprocess and create video data, ensuring its quality, relevance, and appropriateness for training and validation of AI models
  • Performance Optimization: Continuously optimize algorithms for real-time or near-real-time execution, considering computational efficiency and resource constraints
  • Validation and Testing: Design and implement rigorous testing and validation procedures to assess the performance and robustness of developed algorithms under various scenarios and conditions
  • Collaboration: Collaborate closely with cross-functional teams, including software engineers, UI/UX designers, and domain experts, to ensure seamless integration of AI solutions into existing healthcare systems
  • Research and Innovation: Stay up-to-date with the latest advancements in computer vision and AI technologies, and proactively explore new approaches to enhance patient safety and care quality
  • +5 years of relevant experience
  • Strong expertise in computer vision techniques, including object detection, tracking, and image/video analysis
  • Proficiency in programming languages such JavaScript and familiarity with relevant libraries (e.g., TensorFlow JS, OpenCV, PoseNet, Coco SSD)
  • Experience with deep learning frameworks and architectures, including CNNs, RNNs, and attention mechanisms
  • Strong command of React, TypeScript, and JavaScript for integrating web ML models into webapplications
  • Solid understanding of data preprocessing, augmentation, and feature extraction techniques for video data
  • Ability to optimize algorithms for real-time or low-latency execution, considering hardware constraints
  • Deep knowledge of models training, optimization, and investigating best options for a case
  • Experience in deploying AI models in production environments is a plus
  • Excellent problem-solving skills, critical thinking, and attention to detail
  • Level of English Upper-Intermediate and above
project stage

The project has passed the MVP phase. Application is deployed to prod. Active development continues in parallel with production support.

  • 2-week sprint. The input of the process will be sprint backlog, output - functionality increment. The focus here is on the predictable delivery of defined pieces of functionality
  • Continuous exploration process. The input of this process is some custom feature, improvement idea, or need. Output is a team backlog planned through sprints

team composition

2SE, QA, AQA, UI/UX designer, DevOps

Client-side team structure: Product Owner, 2SE

our benefits
  • $600 education budget
  • Health insurance starting on the first working day
  • $600 extra for the health care, sports or mental health
  • Accounting services
  • 20 paid working days off and 10 days sick leave
  • Relocation reimbursement
  • Soulful team buildings and corporate events
work conditions
  • Probationary period:
    3 months
  • Work schedule:
    Flexible working schedule, 8-hours working day, five-day workweek
  • Equipment providing:
    We provide a MacBook Pro and, if necessary, a monitor or other equipment
  • Remote work opportunity:
    We provide the opportunity to work either remotely or from one of our offices
why us
  • No micromanagement or bureaucracy
  • We find out the "Why?" first
  • High quality standard of project development
  • Ability to work in a team of professionals (the ratio of middle and upper specialists is 80/20)
  • Freedom to engage in decision-making and implementation
  • We build a working relationship based on partnership among each other and with our clients
Hiring process:

Hiring process. The hiring process typically involves 2-3 steps, depending on the position: up to a 1-hour interview with HR, a 1.5-hour technical interview, and a final interview.

Overtime policy:

In general, overtimes are not something we practice, but in case of an emergency, and if there is an agreement between the manager and the developer, overtime will be compensated financially.

Office locations:

Ukraine, Lviv, M.Voronoho str., 3; Cherkasy, Shulezhko str., 100.

HR manager
Anastasia Boyko
HR manager
Sofiia Nosar
HR manager
Diana Zherebetska

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