Python Software Engineer — AI/ML Integration & AI Agents

About the Role We are looking for a Python Software Engineer to join our engineering team and work at the intersection of software development, machine learning, and embedded systems. The primary focus of this role is integrating machine learning and neural network models developed by our ML Engineers into production products, as well as developing AI agents, backend services, APIs, and integration layers for internal and external systems. Most of our products run on embedded Linux-based devices, so the role requires a practical engineering mindset with attention to performance, reliability, resource constraints, and deployment. This is primarily a software engineering role, not a model research or Data Scientist position. Location Remote, Europe ( Estonia preferably). Help with relocation possible. Responsibilities Integrate ML and neural network models developed by ML Engineers into production applicationsBuild and maintain Python-based inference pipelines and servicesDevelop software components that connect ML models with existing product functionalityDevelop AI agents and agent-based workflows, including tool calling, external services, and APIsDesign and implement REST APIs / integration APIs for external products and servicesDevelop software for embedded Linux environmentsOptimize inference and application code for devices with limited CPU, memory, storage, or other hardware constraintsIntegrate Python applications with system services, hardware interfaces, databases, message brokers, and external APIsWork with ML Engineers to define model input/output contracts and production inference interfacesPackage and deploy applications and ML componentsImplement logging, monitoring, error handling, and diagnosticsWrite unit and integration testsTroubleshoot issues across application, ML inference, operating system, network, and deployment layersParticipate in architecture and technical design discussionsMaintain technical documentation for implemented components and integrations Required Skills Strong knowledge of Python and practical experience developing production softwareGood understanding of software engineering principles and application architectureExperience building REST APIs and backend services, preferably using frameworks such as FastAPI, Flask, or similarExperience working with LinuxUnderstanding of processes, networking, filesystems, permissions, services, and Linux command-line toolsExperience integrating third-party libraries, SDKs, APIs, or external servicesGood understanding of asynchronous programming, multithreading, or multiprocessing conceptsExperience with Git and standard software development workflowsAbility to debug complex integration issuesUnderstanding of automated testing and code quality practices ML / AI Integration Skills Deep ML research experience is not required, but the candidate should be comfortable working with ML models as software components. Expected knowledge includes: Basic understanding of machine learning and neural networksUnderstanding of the typical ML inference lifecycle:input → preprocessing → model inference → postprocessing → application logicExperience or familiarity with one or more ML frameworks/runtimes such as:PyTorchTensorFlowONNX / ONNX RuntimeTensorRTOpenVINOTFLiteAbility to work with models, tensors, model inputs/outputs, preprocessing pipelines, and inference APIsAbility to collaborate with ML Engineers to move models from experiments into production environments AI Agents Experience with AI agents or LLM-based applications is highly desirable. Relevant experience may include: Building LLM-powered applicationsAgent/tool-calling architecturesIntegration with external APIs and servicesFunction calling and structured outputsRAG systemsMCP or similar tool integration protocolsAgent orchestration frameworks such as LangGraph, LangChain, or similarWorking with commercial or open-source LLM APIs Production experience with these technologies is preferred, but strong Python engineers with relevant backend experience and an interest in agentic systems are also welcome. Embedded / Linux Experience Since many of our products are embedded Linux devices, experience in the following areas would be a strong advantage: Embedded Linux developmentARM-based platformsCross-platform or cross-compilation environmentsWorking with limited compute and memory resourcesLinux services and systemdDevice communication and hardware interfacesDocker on Linux or embedded/edge devicesEdge AI / on-device ML inferencePerformance profiling and optimizationDeep embedded C/C++ experience is not mandatory, but familiarity with embedded development environments is beneficial. DevOps — Basic Knowledge Expected We do not expect the candidate to be a dedicated DevOps Engineer, but basic practical DevOps experience is desirable. Examples include: Docker and containerizationCI/CD pipelinesGitHub Actions, GitLab CI, Jenkins, or similar toolsLinux application deploymentEnvironment and configuration managementBasic networking and troubleshootingApplication logging and monitoringBasic understanding of Kubernetes is a plus Nice to Have C/C++ knowledge and experience integrating Python with native librariesExperience with edge AI or embedded AI systemsExperience optimizing neural network inferenceExperience with NVIDIA Jetson, ARM, NPU, GPU, or similar hardware acceleratorsExperience with gRPC, WebSockets, or event-driven architecturesExperience with MQTT, Kafka, RabbitMQ, or similar messaging technologiesExperience with PostgreSQL, SQLite, Redis, or other databasesExperience with MLflow or other MLOps toolingExperience with microservicesExperience developing SDKs or APIs for third-party integrations What We Are Looking For We are looking for an engineer who is comfortable working between different technical domains: Python development → ML models → Linux → embedded devices → APIs → AI agents → production deployment. You do not need to be an expert in every area. The ideal candidate is a strong Python developer who can take an ML model, prototype, or AI capability and turn it into a reliable, maintainable, production-ready software component. About Sky Spy Sky Spy is a fast-growing dual-use startup developing next-generation RF intelligence solutions for contested environments. We are backed by leading European VCs, combat veterans, and technologists. Our mission is to deliver intelligence that saves lives and empowers allied forces worldwide.