Full-Time ML Engineer/Software Engineer

At Scalable Capital, we're expanding our Data Department with ML Engineering roles. This role focuses on infrastructure (MLOps) or bridging software development and Machine Learning.

Responsibilities:

• Identify, evaluate, implement, and maintain AI/ML technologies for internal and client services, following software engineering best practices.
• Drive architecture development for scalable ML/AI solutions.
• Build infrastructure components, CI/CD pipelines, and maintain ML services on AWS.
• Evaluate retrieval techniques, language models, and generative AI methodologies, focusing on practical solutions.
• Implement automated testing and monitoring for AI system accuracy and reliability.
• Collaborate with cross-functional teams for AI system integration.
• Stay current with industry developments.

Requirements:

• Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field.
• Generalist mindset, open to switching technical domains (Backend, Frontend, AI/ML).
• Extensive AI/ML and software development experience (Python).
• Frontend experience (e.g., Next.js).
• Dockerization, cloud platform experience (AWS: ECS, Lambdas, API Gateway, AWS Bedrock, Sagemaker).
• CI/CD pipeline experience (Jenkins, GitHub Actions).
• Proficiency with modern machine learning libraries (scikit-learn, PyTorch, Transformers, Langchain, LlamaIndex).
• Understanding of chains, routing, agents, Retrieval-Augmented Generation (RAG), and vector databases.
• MLOps knowledge, including ML model lifecycle, deployment, performance monitoring.
• Experience with model training, fine-tuning, evaluation, optimization, and risk mitigation.
• Infrastructure as Code (e.g., Terraform).
• Interest in financial services.
• Strong project management, organizational, problem-solving skills, and hands-on mentality.

Benefits:

• Fast-growing, visible Fintech startup in Europe.
• Innovative services impacting customer lives.
• International, diverse, inclusive team.
• Excellent office location in Munich or Berlin, or remote work within Germany.
• Flexible vacation policy, ability to work abroad.
• Latest hardware and tools.
• In-house knowledge sharing sessions and education budget.

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