Job Description
At Scalable Capital, we are thrilled to expand our Data Department with multiple new ML Engineering roles in our growing Data Science team. Depending on the applicant's profile, this role can either focus more on the infrastructure side (i.e., MLOps) or bridge the gap between software development and Machine Learning . In any case, in this newly formed work stream, you will have the unique opportunity to lay the foundations and set the right direction.
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
Qualifications
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a related fieldA generalist mindset to continuously learn and open to switch between different technical domains like Backend, Frontend, AI / ML InfrastructureExtensive 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, SagemakerFamiliarity with building CI / CD pipelines (e.g., Jenkins, GitHub Actions) and version control practicesConfidence in working with modern machine learning libraries such as scikit-learn, PyTorch, Transformers, Langchain, LlamaIndexStrong understanding of chains, routing, agents, Retrieval-Augmented Generation (RAG), and the use of vector databases for managing structured and unstructured data sourcesFamiliarity with MLOps practices, understanding the lifecycle of ML model development and deployment, performance monitoring and how this can be also applied to LLM use casesIdeally hands on experience with model training, fine-tuning, evaluation, optimization, risk mitigation even in production environmentsExperience with Infrastructure as Code (e.g., terraform)Interest in financial services and markets is a plusStrong project management and organisational skills paired with excellent problem solving skills and hands on mentalityAdditional Information
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 customersWork with an international, diverse, inclusive, and ever-growing team that loves creating the best products for our clientsEnjoy an office in a great location in the middle of Munich, Berlin, or choose to work remotely within Germany (if eligible for the job)Flexible vacation policy and the opportunity to work from abroadBe productive with the latest hardware and toolsLearn and grow by joining our in-house knowledge sharing sessions and spending your individual Education Budget