Lead the design, development, and deployment of advanced probabilistic models and personalization systems to drive pricing and offer decisions at SIXT.
Responsibilities
Architect and prototype advanced regression models with Bayesian approach
Design and productionise personalisation and recommendation systems
Apply SVI, MCMC, and importance sampling for robust decision-making
Build and maintain reproducible pipelines for feature engineering and automated data validation
Deploy models via FastAPI, Docker, or Kubeflow and establish real-time monitoring
Requirements
Nice to have: Recommender systems
Nice to have: Two-tower retrieval
Nice to have: Embedding-based candidate generation
Infrastructure Engineer based in Austin, TX, responsible for building and running Harmattan AI’s U.S. infrastructure across networking, cloud, identity, endpoints, and user support.
Responsibilities
Help design, deploy, and maintain infrastructure spanning networking, cloud, identity, and endpoints
Help implement and document security and compliance requirements across the environment
Review and test work delivered by vendors and integrators against technical requirements before go-live
Set up and manage Windows, Mac, and Linux devices, ensuring they are secure and meet company policies
Support cloud environments and virtual desktop infrastructure, and automate repetitive work through scripting and infrastructure as code
Requirements
Hands‑on experience matters more than field of study
The starting salary range posted for this position is $149,100.00 to $218,100.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits.
Responsibilities
Partner with enterprise customers to understand technical requirements and business goals.
Design scalable AI solution architectures and guide customers through production deployments.
Build integrations, prototypes, and reusable tools that accelerate customer success.
Lead technical workshops, architecture discussions, and troubleshoot complex production issues.
Collaborate with Product and Engineering teams to share customer feedback and influence future product enhancements.
Requirements
Bachelor's in Computer Science
Nice to have: Deploying or supporting Generative AI, LLM, or Machine Learning applications in production
Nice to have: Experience with Kubernetes, cloud infrastructure, observability, or MLOps
Nice to have: Experience building customer-facing technical solutions or integrations
Nice to have: Experience creating reusable developer tools, frameworks, or open-source contributions
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