Locations

• Bulgaria
• Georgia
• Lithuania
• Mexico
• Moldova
• Poland
• Romania
• Ukraine

Company Background

The client is a healthcare technology company on a mission to improve outcomes through data-driven insights. With a focus on delivering industry-leading Patient-Reported Outcome Measures (PROMs) adoption rates, the company empowers providers with tools for smarter operations and better care. Their current AI maturity presents a greenfield opportunity for technical leaders eager to define and implement strategic AI solutions in a collaborative and fast-paced environment.

Project Description

The project centers around developing a suite of AI-powered tools within a healthcare platform. These tools aim to enhance patient engagement, automate communication via sentiment-aware CRM integration, process unstructured device data using GenAI, and surface predictive analytics to detect early signs of patient risk. Additionally, a natural language-driven insights interface enables dashboard generation and anomaly detection to improve care quality, reduce operational costs, and increase platform engagement.

Technologies

• Python
• FastAPI
• Django (DRF)
• PyTorch
• TensorFlow
• Hugging Face
• OpenAI
• Bedrock
• Docker
• AWS (ECR, ECS, EC2, Lambda)
• CI/CD
• MLflow
• SQL
• NoSQL
• Vector Stores
• Pandas
• OpenCV
• Kafka
• RabbitMQ
• Kubernetes
• AWS SageMaker
• Apache Spark
• Dask
• Azure
• GCP

What You'll Do

• Architect, develop, and deploy ML solutions aligned with cost-reduction and revenue-growth KPIs;

• Own the full ML lifecycle including data acquisition, model training, evaluation, A/B testing, and production deployment;

• Translate business objectives into robust technical solutions in collaboration with stakeholders;

• Refactor and modernize legacy components into scalable infrastructure;

• Ensure high code quality through strong testing and observability practices;

• Lead demos and workshops for business and technical audiences;

Job Requirements

• Minimum 3+ years of experience in machine learning or data engineering roles;

• Solid theoretical foundation in machine learning, natural language processing (NLP), and computer vision;

• Strong Python development skills and experience building end-to-end ML/NLP/CV pipelines in production environments;

• Proven experience deploying ML systems in cloud environments, preferably AWS (ECR, ECS, EC2, Lambda, Bedrock);

• Hands-on experience with containerization tools like Docker and orchestration in production settings;

• Familiarity with distributed systems and message-based architectures; Kafka experience is a plus;

• Experience setting up and maintaining CI/CD pipelines and version control workflows using modern DevOps practices;

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Internal startup incubator;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.