Senior AI/ML Engineer

This is a fully remote position, open to applicants in Belgium, +2 more countries.

📋 Description

• Design and enhance the multi-agent orchestration platform, which includes plugins, tool-use pipelines, observability hooks, as well as voice, telephony, and messaging channel adapters.

• Create and execute voice AI pipelines utilizing STT, real-time streaming TTS, VAD, and SIP/RTP telephony integration while aiming for sub-300 ms latency targets.

• Develop and sustain RAG pipelines that incorporate retrieval quality measurement, re-ranking, and a combination of vector and keyword search.

• Establish MCP server architecture and tool-use agreements for both internal and external integrations.

• Refine and assess LLMs using LoRA, QLoRA, and DPO for applications in customer support, classification, and structured extraction.

• Evaluate model quality through automated assessments, human preference data, and metrics specific to speech/RAG.

• Oversee the model lifecycle, experiment tracking, versioning, reproducibility, and the promotion of models into production.

• Lead AI observability initiatives with Langfuse tracing, LLM call instrumentation, cost monitoring, and quality regression alerting.

• Establish and implement guidelines for hallucination detection, PII redaction, output safety scanning, and rate limiting.

• Construct data ingestion, preprocessing, feature extraction, and continual-learning pipelines.

• Propel ML CI/CD processes, including automated evaluation gates, shadow deployments, canary releases, and rollback triggers.

• Set AI architectural benchmarks, conduct design evaluations, and maintain ADRs.

• Guide and mentor ML engineers and applied scientists.

• Collaborate with Product and Commercial teams to convert business challenges into ML formulations and success criteria.

• Partner with external research collaborators and keep abreast of emerging research and open-source advancements.

⛳️ Requirements

• Over 8 years of experience in ML Engineering, Applied AI, or Research Engineering.

• A minimum of 2 years in a lead or staff-level position.

• Extensive hands-on production experience with LLMs, including fine-tuning, RLHF/DPO, prompt engineering, RAG, and tool utilization.

• Proficient in Python and experienced with PyTorch, HuggingFace Transformers, and PEFT/LoRA.

• Familiarity with LLM inference serving using vLLM, TensorRT-LLM, or TGI in a latency-sensitive production environment.

• Practical understanding of agentic frameworks, multi-agent coordination, tool-call orchestration, context/memory management, and observability.

• Solid grasp of MLOps, encompassing MLflow/W&B, Docker/Kubernetes, model registries, and CI/CD for ML.

• Awareness of LLM-specific risks and production mitigations, such as hallucination, prompt injection, data leakage, fairness, and privacy.

• Excellent communication skills for design documentation, architecture reviews, and discussing trade-offs with non-technical stakeholders.

• Proof of eligibility to work in the country of application.

• Experience with speech AI or real-time audio systems is a significant advantage.

• Familiarity with voice pipelines, multi-hop RAG, MCP, open-source ML contributions, multimodal models, or quantization techniques is a plus.

🏝️ Benefits

• No relocation packages or visa sponsorship provided.

• Commitment to diversity and inclusion.

• Initiatives focused on ESG and sustainability.