Edge Solutions Lab

WHO WE ARE

We are Edge Solutions Lab, a team of engineers with a strong background in product development of edge solutions and data platforms. Our legacy is grounded in the successful execution of the Hivecell product. We're committed to helping companies implement their product strategies and turn data into real, measurable value.

WHO WE ARE LOOKING FOR

We are seeking a skilled NATS Expert to join an exciting project for our client, Flow — a forward-thinking company transforming the way people live, work, and connect. You will play a key role in building and evolving the messaging infrastructure that powers Flow's distributed cloud and edge platform products, ensuring data flows reliably, securely, and at scale across their production-grade environment.

KEY RESPONSIBILITIES

• Design, deploy, and maintain NATS and NATS JetStream infrastructure for high-throughput, low-latency messaging
• Architect messaging topologies that support distributed, multi-tenant, and edge computing environments
• Define and enforce best practices around subject design, security (NKeys, JWTs, accounts), and message delivery guarantees
• Collaborate with product and engineering teams to integrate NATS into data pipelines, microservices, and edge platforms
• Monitor, troubleshoot, and optimize NATS clusters for performance, resilience, and observability
• Develop and maintain tooling, configuration management, and automation around NATS deployments
• Participate in architecture reviews and provide expertise on messaging patterns and trade-offs

WHAT YOU BRING ALONG

• 4+ years of professional experience working with NATS in production environments
• Deep knowledge of NATS core concepts: subjects, queues, consumers, JetStream, Key-Value store, and Object Store
• Hands-on experience with NATS cluster configuration, leaf nodes, and super-cluster topologies
• Solid understanding of NATS security model: accounts, NKeys, JWT-based authentication, and authorization
• Experience integrating NATS with Go, Python, or other languages via official NATS client libraries
• Proficiency with observability tooling — metrics, tracing, and alerting for distributed messaging systems
• Strong understanding of distributed systems fundamentals: consistency, fault tolerance, backpressure, and message ordering
• Experience with containerized and Kubernetes-based deployments (Helm, operators, or custom manifests)
• Practical experience leveraging AI-powered tools (e.g., GitHub Copilot, ChatGPT, or similar) to enhance productivity and accelerate development workflows
• English proficiency at B2 level or higher — able to communicate effectively in a professional setting, both written and spoken

WILL BE A PLUS

• Experience with edge computing or IoT messaging architectures
• Familiarity with other messaging systems (Kafka, RabbitMQ, MQTT) and ability to compare trade-offs
• Contributions to the NATS ecosystem or open-source projects
• Experience with multi-cloud or hybrid infrastructure environments
• Knowledge of data streaming patterns and event-driven architecture

SOFT SKILLS

• Strong systems thinking and ability to reason about complex distributed environments
• Ownership mindset — proactive in identifying issues and driving them to resolution
• Clear and structured communication, able to articulate architectural decisions to both technical and non-technical audiences
• Collaborative and open to feedback in cross-functional team settings
• Attention to detail and a commitment to operational excellence
• Comfort with ambiguity and confidence navigating fast-changing technical requirements

WHO WE ARE

We are Edge Solutions Lab, a team of engineers with a strong background in product development of edge solutions and data platforms. Our legacy is grounded in the successful execution of the Hivecell product. We're committed to helping companies implement their product strategies and turn data into real, measurable value.

WHO WE ARE LOOKING FOR

We are seeking an experienced Data Scientist to join an exciting project for our client, Flow — a forward-thinking company transforming the way people live, work, and connect. You will work on real-world data challenges at the intersection of edge computing and data platforms, turning complex, large-scale data into models and insights that directly shape Flow's digital ecosystem and drive measurable product value.

KEY RESPONSIBILITIES

• Design, develop, and deploy machine learning models and statistical solutions that address real business problems
• Collaborate with product, engineering, and domain teams to translate requirements into data-driven solutions
• Conduct exploratory data analysis and feature engineering on large, complex datasets
• Build and maintain scalable data pipelines to support model training, evaluation, and inference
• Define and track model performance metrics; monitor models in production and drive continuous improvement
• Communicate findings, methodologies, and results clearly to both technical and non-technical stakeholders

• Contribute to the team's data science best practices, tooling, and documentation

   

WHAT YOU BRING ALONG

• 4+ years of professional experience as a Data Scientist or in a similar role
• Strong proficiency in Python and core data science libraries (pandas, NumPy, scikit-learn, etc.)
• Solid understanding of machine learning algorithms, statistical modeling, and model evaluation techniques
• Experience with deep learning frameworks (TensorFlow or PyTorch) is expected at this level
• Hands-on experience deploying models to production environments (REST APIs, containerization, cloud platforms)
• Proficiency with SQL and working with relational or distributed data stores
• Familiarity with MLOps practices: experiment tracking, model versioning, monitoring (e.g., MLflow, Weights & Biases)
• Experience working with cloud platforms such as AWS, GCP, or Azure
• Practical experience leveraging AI-powered tools (e.g., GitHub Copilot, ChatGPT, or similar) to enhance productivity and accelerate development workflows
• Working knowledge of: graph databases (Memgraph, Neo4j, or similar); edge inference runtimes (ONNX Runtime, llama.cpp, ExecuTorch); gradient boosting frameworks (XGBoost, LightGBM, CatBoost); time-series analysis on IoT or sensor data streams; Snowflake and dbt-based analytics pipelines
• English proficiency at B2 level or higher — able to communicate effectively in a professional setting, both written and spoken

WILL BE A PLUS

• Experience with edge computing or IoT data streams
• Knowledge of time-series analysis and anomaly detection
• Familiarity with data orchestration tools (Airflow, Prefect, or similar)
• Contributions to open-source projects or published research
• Experience in a product-focused or startup environment

SOFT SKILLS

• Strong analytical thinking with a pragmatic, solution-oriented mindset
• Ability to work independently and take ownership of tasks end-to-end
• Clear and concise communication — able to explain complex concepts to non-technical audiences
• Collaborative attitude and comfort working in cross-functional teams
• Intellectual curiosity and a continuous drive to learn and improve
• Comfort with ambiguity and the ability to prioritize effectively in a fast-paced environment