Senior Ml Engineer, Software Engineer

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Scalable

๐Ÿ“Remote - Germany

Job highlights

Summary

Join Scalable Capital's Data Department as an ML Engineer and contribute to the development and implementation of cutting-edge AI/ML technologies. This role offers the unique opportunity to build foundational infrastructure and shape the direction of a newly formed work stream. Responsibilities include identifying, evaluating, and maintaining AI/ML technologies, developing scalable solutions, building infrastructure components, and collaborating with cross-functional teams. The ideal candidate possesses a strong background in AI/ML, software development, and cloud platforms, along with experience in MLOps and CI/CD pipelines. Scalable Capital offers a dynamic work environment, flexible work arrangements, and opportunities for professional development.

Requirements

  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related field
  • A generalist mindset to continuously learn and open to switch between different technical domains like Backend, Frontend, AI/ML Infrastructure
  • Extensive experience in AI/ML technologies and software development (Python)
  • Experience with building frontends (e.g., Next.js would be a big plus)
  • Experience with dockerization, cloud platforms, preferably AWS (ECS, Lambdas, API Gateway,...), and related ML/GenAI services such as AWS Bedrock, Sagemaker
  • Familiarity with building CI/CD pipelines (e.g., Jenkins, GitHub Actions) and version control practices
  • Confidence in working with modern machine learning libraries such as scikit-learn, PyTorch, Transformers, Langchain, LlamaIndex
  • Strong understanding of chains, routing, agents, Retrieval-Augmented Generation (RAG), and the use of vector databases for managing structured and unstructured data sources
  • Familiarity with MLOps practices, understanding the lifecycle of ML model development and deployment, performance monitoring and how this can be also applied to LLM use cases
  • Experience with Infrastructure as Code (e.g., terraform)
  • Strong project management and organisational skills paired with excellent problem solving skills and hands on mentality

Responsibilities

  • Identify, evaluate, implement, and maintain (Gen) AI / ML technologies for internal but also potential future client-serving services by following software engineering best practices
  • Drive the development of appropriate architectures for deploying and maintaining scalable ML/(Gen) AI solutions
  • Build infrastructure components, CI/CD pipelines, configure, extend, and maintain our existing ML services on AWS
  • Evaluate retrieval techniques, language models, and generative AI methodologies by not losing your focus on pragmatic solutions
  • Implement automated testing and monitoring techniques to ensure the accuracy and reliability of AI systems
  • Collaborate with cross-functional teams to ensure the successful integration of AI systems into business processes
  • Stay up to date with the latest industry developments and technologies to ensure our solutions remain at the forefront of innovation

Preferred Qualifications

  • Ideally hands on experience with model training, fine-tuning, evaluation, optimization, risk mitigation even in production environments
  • Interest in financial services and markets is a plus

Benefits

  • Be part of one of the fastest-growing and most visible Fintech startups in Europe, creating innovative services that have a substantial impact on the lives of our customers
  • Work with an international, diverse, inclusive, and ever-growing team that loves creating the best products for our clients
  • Enjoy an office in a great location in the middle of Munich, Berlin,ย or choose to work remotely within Germanyย (if eligible for the job)
  • Flexible vacation policy and the opportunity to work from abroad
  • Be productive with the latest hardware and tools
  • Learn and grow by joining our in-house knowledge sharing sessions and spending your individual Education Budget

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