Senior AI/ML Engineer

Job not on LinkedIn

🔥 1 minute ago

🌐 Belgium, Italy, +1 more countries – Remote

🇧🇪 Belgium – Remote 🇮🇹 Italy – Remote 🇩🇪 Germany – Remote

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 10%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

Apply Now

Find Similar Remote Jobs

Set Up Email Alert For New Jobs

📊 Check your resume score for this job

Improve your chances of getting an interview by checking your resume score before you apply.

Upload Resume

team.blue

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

💼 Consulting

📣 Marketing

📦 Logistics

Consulting • Marketing • Logistics

team. blue is a leading digital enabler for companies and entrepreneurs, serving over 3. 3 million customers across Europe. With a team of more than 2000 experts, they provide innovative digital services aimed at empowering businesses through technology. team. blue operates a variety of brands and focuses on delivering excellent customer experiences.

📋 Description

• Architect and evolve the multi-agent orchestration platform, including plugins, tool-use pipelines, observability hooks, and voice, telephony, and messaging channel adapters • Design and implement voice AI pipelines using STT, real-time streaming TTS, VAD, and SIP/RTP telephony integration with sub-300 ms latency targets • Build and maintain RAG pipelines with retrieval quality measurement, re-ranking, and hybrid vector and keyword search • Define MCP server architecture and tool-use contracts for internal and third-party integrations • Fine-tune and evaluate LLMs using LoRA, QLoRA, and DPO for customer support, classification, and structured extraction • Benchmark model quality using automated evaluations, human preference data, and speech/RAG-specific metrics • Manage model lifecycle, experiment tracking, versioning, reproducibility, and production promotion • Own AI observability with Langfuse tracing, LLM call instrumentation, cost tracking, and quality regression alerting • Define and enforce guardrails for hallucination detection, PII redaction, output safety scanning, and rate limiting • Build data ingestion, preprocessing, feature, and continual-learning pipelines • Drive ML CI/CD, including automated evaluation gates, shadow deployments, canary releases, and rollback triggers • Set AI architectural standards, conduct design reviews, and own ADRs • Mentor ML engineers and applied scientists • Collaborate with Product and Commercial teams to translate business problems into ML formulations and success metrics • Engage with external research partners and monitor emerging research and open-source developments

🎯 Requirements

• 8+ years in ML Engineering, Applied AI, or Research Engineering • At least 2 years in a lead or staff-level role • Deep, hands-on production experience with LLMs, including fine-tuning, RLHF/DPO, prompt engineering, RAG, and tool use • Fluent in Python and experienced with PyTorch, HuggingFace Transformers, and PEFT/LoRA • Experience with LLM inference serving using vLLM, TensorRT-LLM, or TGI in a latency-sensitive production environment • Practical knowledge of agentic frameworks, multi-agent coordination, tool-call orchestration, context/memory management, and observability • Solid understanding of MLOps, including MLflow/W&B, Docker/Kubernetes, model registries, and CI/CD for ML • Awareness of LLM-specific risks and production mitigations, including hallucination, prompt injection, data leakage, fairness, and privacy • Strong communication skills for design documentation, architecture reviews, and explaining tradeoffs to non-technical stakeholders • Proof of eligibility to work in the country applied for • Experience with speech AI or real-time audio systems is a strong plus • Experience with voice pipelines, multi-hop RAG, MCP, open-source ML contributions, multimodal models, or quantization techniques is nice to have

🏖️ Benefits

• No relocation packages or visa sponsorship • Diversity and inclusion commitment • ESG and sustainability initiatives