Senior Backend Engineer – AI, Machine Learning

This is a fully remote position, open to applicants in Germany.

📋 Description

• Design, develop, and implement machine learning features within production environments.

• Construct dependable data pipelines for processing, transforming, and preparing data for machine learning models, analytics, and intelligent product functionalities.

• Develop internal (gRPC) and external (REST) APIs that facilitate the consumption of AI/ML services by other applications and systems.

• Assist in experimentation, validation, monitoring, and continuous enhancement of ML models and AI-driven features.

• Ensure that ML-powered features are reliable, efficient, maintainable, and designed for scalability.

• Collaborate closely with product managers, backend engineers, frontend engineers, QA, and design teams to define, refine, and deliver intelligent product experiences.

• Take ownership of AI and ML capabilities from technical discovery and prototyping through to production deployment, monitoring, maintenance, and iteration.

• Work with DevOps and backend teams to deploy, monitor, and scale ML-powered services in AWS cloud environments.

• Utilize coding agents and AI development tools to enhance development speed, testing, documentation, and code quality, while maintaining accountability for architecture, security, reliability, and production outcomes.

• Create and maintain dedicated AI/ML services, primarily utilizing Python and modern backend engineering practices.

• Integrate, serve, and sustain ML models within scalable backend systems and microservices architectures.

• Establish evaluation criteria, test datasets, monitoring, tracing, and quality metrics for AI-powered features.

• Identify potential failure modes and implement suitable safeguards and fallback behaviors.

⛳️ Requirements

• Over 5 years of backend development experience using Python, with a preference for Java Spring Boot.

• Strong practical experience with Python and widely used ML/data libraries and frameworks.

• Proven experience in building and deploying production-quality machine learning features, beyond mere experiments or notebooks.

• Comprehensive understanding of data pipelines, model serving, APIs, and backend system integration.

• Familiarity with MLOps tools and workflows, as well as cloud infrastructure, preferably AWS.

• Knowledge of microservices architecture and contemporary backend engineering practices in Java.

• Understanding of ML lifecycle concepts, including training, evaluation, deployment, monitoring, and iteration.

• Experience with databases, data processing, and both structured and unstructured data.

• Familiarity with NLP, RAG, LLMs, recommendation systems, prediction models, vector databases, embeddings, agentic AI systems, tool calling, workflow orchestration, or other applied AI/ML domains is a strong advantage.

• Capable of translating complex data and ML concepts into practical, usable product features.

• Strong problem-solving abilities and a pragmatic engineering mindset.

• Hands-on experience with AI coding tools or agents as part of a professional software development workflow.

• Experience in evaluating AI or ML systems through automated tests, offline evaluations, production metrics, and human feedback.

• Excellent communication skills and the ability to work collaboratively with both technical and non-technical stakeholders.

• Languages: Proficient in English to integrate seamlessly with our international team and clientele. Knowledge of Spanish is advantageous, particularly as the product targets the Latin American market.

🏝️ Benefits

• Flexibility

• Remote work & Tooling

• Culture

• Autonomy and responsibility