KI
Senior Platform Engineer at Kiln designing and deploying cloud infrastructure. Collaborating with teams to ensure robust delivery in a fast - paced fintech environment.
About the role
- Own end-to-end AI/ML pipeline, including CI/CD processes for ML and AI engineering workflows
- Manage code, version datasets, foundation and fine-tuned models, AI agents, and production endpoints to enable ML Engineers to collaborate and scale
- Design and maintain automated pipelines for both traditional ML models and modern AI systems including LLMs, multimodal models, and AI agents
- Implement robust CI/CD practices for model training, fine-tuning, evaluation, and deployment across diverse AI workloads
- Orchestrate deployment of models, AI agents, and inference endpoints with automated testing and rollback capabilities
- Build and maintain infrastructure for large language model inference, fine-tuning, and serving at scale
- Implement comprehensive monitoring for model performance, drift detection, AI safety metrics, and responsible AI compliance
- Evolve operational processes to support both traditional ML and cutting-edge AI technologies
Requirements
- 4+ years of industry experience building and deploying production-grade AI/ML systems
- Recent hands-on engineering experience with AI/LLM infrastructure and tooling (pure ML modelling is not required)
- Strong proficiency with Python, and familiarity with Scala, Go, or Rust
- Cloud platform expertise with AWS, GCP, or Azure, including AI-specific services (SageMaker, Vertex AI, Azure AI)
- Databricks platform experience with Unity Catalog, MLflow, and Databricks Machine Learning for end-to-end AI/ML workflows
- Modern ML infrastructure experience with tools like MLflow or similar platforms
- Containerization & orchestration experience with Docker, Kubernetes, and ML-specific operators
- AI model serving experience with modern inference servers and API gateways for AI applications
- Infrastructure as Code experience with Terraform, Ansible, or any other IaC tool of choice (nice to have)
- Distributed computing experience with Databricks, Ray, or Spark for large-scale AI workloads (nice to have)
- AI safety & governance experience with model evaluation, bias detection, and responsible AI practices (nice to have)
- Multi-modal AI experience with vision-language models, speech processing, or other modalities (nice to have)
- Experience at the Tier-1 product company or related experience working within the product organisation (nice to have)
Benefits
- Competitive salary and annual reviews
- Opportunity to participate in Flo’s performance incentive scheme
- Paid holiday, sick leave, and female health leave
- Enhanced parental leave and pay for maternity, paternity, same-sex and adoptive parents
- Accelerated professional growth through world-changing work and learning support
- Flexible office + home working, up to 2 months a year working abroad
- 5-week fully paid sabbatical at 5-year Floversary
- Flo Premium for friends & family, plus more health, pension and wellbeing perks
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