Remote job
Senior AI/ML Engineer
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About this role
Role overview Lead the design and delivery of production AI systems across the full lifecycle, from model adaptation and evaluation to agent orchestration, inference and operational reliability. The scope includes conversational and voice experiences, retrieval systems, integrations and model quality controls. You’ll set technical direction while contributing hands-on to systems used across a large digital services environment.
Responsibilities - Architect and improve multi-agent orchestration, including plugins, tool-use workflows, observability and voice, messaging or telephony channels. - Design real-time voice pipelines spanning speech recognition, speech generation, voice activity detection and telephony integration, with demanding latency targets. - Build retrieval-augmented generation systems with hybrid search, reranking and measurable retrieval quality. - Define integration patterns for model tools and internal or external services. - Fine-tune and evaluate language models for tasks such as support, classification and structured data extraction; manage experiments and production releases. - Establish monitoring and safeguards for model quality, cost, hallucinations, fairness and privacy.
Requirements - Senior hands-on experience taking AI or machine learning systems from design through production operation. - Practical expertise in language models, fine-tuning and evaluation, with reproducible model lifecycle practices. - Experience building agentic systems, retrieval pipelines or real-time inference services. - Ability to design observability, reliability measures and production guardrails for AI applications. - Strong written and verbal communication, including design documents and architecture discussions.
Nice to have End-to-end voice AI experience; advanced retrieval approaches; Model Context Protocol server design; multimodal models; model quantization; or open-source or research contributions. Speech evaluation methods and retrieval-specific quality measures are also relevant.