Senior Machine Learning Engineer - Syte at Nayax

Herzliya, Tel-Aviv District, Israel -

Full Time

Start Date

Immediate

Expiry Date

27 May, 26

Salary

0.0

Posted On

26 Feb, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Machine Learning, System Architecture, CI/CD, Kafka, MongoDB, OpenSearch, Docker, Kubernetes, Node.js, AirFlow, Model Serving, Event-Driven Systems, Data Streaming, Performance Reliability, Fault Tolerance

Industry

Financial Services

Description

Join us at Nayax, 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 Nayax, you’ll 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 - mostly for fashion vertical. 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 Why Join Nayax: Work on cutting-edge AI at scale — Syte's image recognition and recommendation platform serves leading retailers worldwide, giving you the opportunity to build ML systems that reach millions of end users. Own the full ML lifecycle — from model serving and retraining pipelines to distributed architecture and observability, this is a role with real depth and end-to-end ownership. Take ownership of your work and make a real impact on our customers — you'll architect and ship ML systems that power real-time product discovery and recommendations for global retail brands. Join a fast-growing global fintech company that values innovation, teamwork, and exceeding customer expectations — with 1,200+ employees across 12 offices and operations in 120+ countries, Nayax is a NASDAQ-listed company at the forefront of AI-powered commerce. Be based at our vibrant Herzliya HQ — collaborate with a large, innovative engineering team of 600+ employees, just a short walk from the train station Learn More about Nayax Nayax is a global fintech company (NASDAQ; TASE: NYAX) providing an end-to-end platform for payments, consumer engagement, and business operations. Founded in 2005, Nayax empowers businesses to grow revenue, reduce operational costs, and deliver seamless commerce experiences. Our customer-first mindset and commitment to in-house innovation have positioned us at the forefront of the cashless payment revolution, serving the unattended and retail sectors around the world. We support over 80 payment methods in 50+ currencies, hold a European payment institution license, and have formed strategic partnerships with global financial institutions to deliver powerful, scalable solutions. With more than 1,200 employees across 12 global offices, Nayax operates in 62+ countries. Our global headquarters in Herzliya Hills, Israel, is our largest site, housing over 600 employees across 20+ departments — just a short walk from the train station and designed for collaboration and growth. At Nayax, we believe in creating long-term impact through loyalty tools, omnichannel solutions, and an agile ecosystem of value-added services. We're proud to support businesses in reaching new heights and we're always looking for innovative, passionate individuals to join us.

Responsibilities

The Senior Machine Learning Engineer will be responsible for architecting and developing high-performance, scalable Machine Learning Engineering services using Python, and collaborating with Data Science teams to productionize ML models through serving, monitoring, and retraining pipelines. Key tasks also involve building and maintaining CI/CD pipelines, designing distributed system architecture, and optimizing integrations with technologies like Kafka, MongoDB, and OpenSearch.