Senior ML Engineer

• Refactor and upgrade existing ML models, including NLP, generative AI and transcription models, into standardised, production-ready modular contracts
• Engineer resilient ML workflows using DAG-based orchestration tools such as Argo Workflows and Airflow
• Ensure robust retry logic, error handling and repeatable execution across ML workflows
• Define, automate and maintain strict ML evaluation pipelines using golden datasets
• Ensure new models meet baseline quality and performance thresholds before release
• Design and implement tracking mechanisms to capture precise model, prompt and input data provenance for full auditability and reproducibility
• Build infrastructure for shadow testing and A/B testing on live traffic
• Implement reliable fallback and kill-switch mechanisms to support safe deployment
• Engineer structured feedback pipelines that capture human reviews and corrections to continuously enrich and refine training datasets
• Integrate third-party AI APIs and manage adapter interfaces
• Implement granular telemetry to track compute costs, token usage and latency

• Proven track record operating at the intersection of Machine Learning, MLOps and Platform/Backend Engineering
• Deep understanding of evaluation metrics for generative AI, LLMs and/or speech models, including Precision, Recall, F1, WER/CER, groundedness and hallucination rates
• Strong hands-on experience with containerisation using Docker and Kubernetes, alongside modern orchestration frameworks
• Experience building observable ML systems with logging, monitoring and strict cost-attribution tracking
• Familiarity with data provenance, compliance standards and building fail-safe mechanisms for sensitive data and AI outputs

• Full-time, long-term role
• Remote-first work environment
• Genuine community focused on growth and well-being
• Opportunities for personal and professional growth
• Teams that invest in employee success