Join us at our company, a global fintech leader (NASDAQ; TASE: NYAX) revolutionizing the world of cashless payments, consumer engagement, and business management solutions. With more than 1,200 employees across 12 offices worldwide. At our company, youll be part of a diverse and innovative community where your work makes a real impact and helps shape the future of payments.
Syte is an image recognition solution for retailers in different verticals such as fashion, home, furniture, DIY etc. We offer AI-powered product recommendation and discovery platform. Our solutions include visual search, automated product tagging, advanced personalized recommendations, and more.
We are currently looking for a Senior Machine Learning Engineer to design and implement scalable and integrate machine learning solutions into production. You will work with modern technologies like Node.js, Python, Kafka, MongoDB, and OpenSearch, AirFlow, while driving architectural decisions and CI/CD best practices. This role combines backend engineering excellence with ML deployment expertise.
The Senior Machine Learning Engineer will report directly to the Director of R&D.
Your key responsibilities will include:
Architect and develop MLE services using Python, ensuring high performance, reliability, and scalability.
Collaborate with Data Science teams to productionize ML models (model serving, monitoring, retraining pipelines).
Build and maintain CI/CD pipelines for automated testing, deployment, and monitoring.
Design and implement system architecture for distributed, event-driven systems.
Integrate and optimize Kafka for real-time data streaming and event processing.
Design and manage MongoDB schemas and queries for optimal performance.
Implement and maintain OpenSearch clusters for search and analytics use cases.
Ensure security, observability, and fault tolerance across all services.
Mentor team members and contribute to engineering best practices.
Requirements: What Makes You a Great Fit:
Minimum 6+ years of backend development experience - Must
Experience with Machine Learning - Must.
Strong expertise in Python for production systems - Must.
Proven experience in system architecture for distributed applications.
Hands-on experience with CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, etc.).
Deep knowledge of Kafka (producers, consumers, partitioning, scaling).
Proficiency with MongoDB (schema design, indexing, aggregation).
Experience with OpenSearch/Elasticsearch (indexing, queries, performance tuning).
Solid understanding of containerization (Docker) and cloud deployment (Kubernetes or similar).
Nice-to-Have
Experience with Argo CD and GitOps workflows, and AirFlow.
Knowledge of ML lifecycle tools (MLflow, Kubeflow, TensorFlow Serving).
Observability stack: Prometheus, Grafana, OpenTelemetry.
Performance optimization and distributed systems troubleshooting.
Tech Stack
Backend: Node.js, Python, REST/GraphQL APIs
Data: MongoDB, Kafka, OpenSearch
Infra: Docker, Kubernetes, CI/CD pipelines
Bonus: Argo CD, Erlang/Elixir, ML deployment frameworks.
This position is open to all candidates.