Skills
Ordered by where my attention actually goes. Research questions first, then the machine learning and AI work they feed, then the infrastructure that carries it.
- Reinforcement learningRLHF and preference optimisationTransformer architecturesAttention and long-context modellingCognitive architectures for language agentsAgent memory: working, episodic, semantic, proceduralAgent scaffolding and harnessesContext managementSelf-refinement and self-correctionReasoning reliability and evaluation
- PyTorchTensorFlowDeep learningTraining and fine-tuningInference and model servingBenchmarking and error analysis
- LLM application developmentAI agentsRetrieval-augmented generation (RAG)Model Context Protocol (MCP)Prompt engineeringEvaluation frameworksAnthropic and OpenAI APIsOllama
- PythonTypeScriptGoJavaScriptRustC++Java
- KubernetesTerraformDockerAzureAWSGCPLinux
- REST APIsMicroservicesEvent-driven architectureDistributed systems
- PrometheusGrafanaDrift detectionExperiment trackingCI/CD
- PostgreSQLMongoDBMySQLClickHouse