Forward Deployed ML Engineer, Agents

aion

Hands-on AI engineer designing and implementing production-grade multimodal AI systems for a fast-growing startup. Collaborating directly with clients to develop intelligent solutions.

Posted 7/14/2026full-timeLondon • 🇬🇧 United KingdomMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying production-grade AI/ML systems, particularly in multimodal AI, voice agents, and LLM applications. Proficient in optimizing real-time systems and integrating advanced AI solutions into customer environments.

Highest-signal resume keywords

Production AI/ML Systems DevelopmentMultimodal AI ExpertiseLLM Application DeploymentAgent Framework ProficiencyMLOps & Deployment

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Hard Skills

Python ProgrammingJavaScript/TypeScript DevelopmentVoice AI Systems IntegrationRAG ImplementationComputer Vision TechniquesModel Fine-TuningInference OptimizationReal-Time Systems OptimizationData Architecture DesignPrototyping and POC Development

Soft Skills

Exceptional CommunicationCustomer-Facing Experience

Tools & Technologies

DockerKubernetesAWSAzureGCPLangChainLlamaIndexREST APIsGraphQLWebSocket

Industry Keywords

AI StrategyTechnical AssessmentsProductionizationObservability ToolingReal-Time Streaming Protocols

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformGraphQLJavaScriptKubernetesPythonTypeScript

About the role

Key responsibilities & impact

Work directly at customer sites from factory floors to executive offices conducting discovery workshops and technical assessments to identify high-impact AI opportunities
Design and architect end-to-end multimodal agent systems (voice + video + text) that leverage aion's distributed GPU infrastructure and managed services
Build production-grade voice AI systems using STT, TTS APIs, and LLMs deployed on aion's platform
Develop vision-enabled agents processing real-time video streams using computer vision pipelines on aion's infrastructure
Implement sophisticated multi-agent orchestration with(or similar) frameworks like LangChain or LlamaIndex—enabling tool use, memory management, and autonomous task completion
Rapidly prototype POCs in 2-4 weeks, coding alongside client teams to validate concepts and iterate based on feedback
Optimize for sub-500ms latency, natural conversation flow, turn detection, and interruption handling in real-time systems
Integrate agents directly into customer codebases via REST/GraphQL/WebSocket APIs and custom SDKs (Python, TypeScript)
Act as trusted technical advisor to customers, shaping AI strategy and guiding roadmap decisions from concept to production
Design data architectures with efficient processing pipelines and ingestion workflows for training and inference on aion's platform
Implement RAG systems with vector databases optimizing embedding strategies, chunk sizes, and retrieval methods
Prepare and validate datasets for fine-tuning, evaluation, and synthetic data generation
Work with other MLEs, MLOps, SREs to carry out model deployment and productionization
Implement LLM and agents observability and monitoring tracking token usage, latency, costs, and quality metrics across deployments on aion's infrastructure
Instrument applications to trace LLM calls, retrieval operations, agent actions, and data flows
Build evaluation frameworks with offline benchmarks (accuracy, relevance, safety metrics) and online monitoring (user feedback, drift detection)

Requirements

What you’ll need

3-5+ years of hands-on experience building production AI/ML systems, with 1-2+ years deploying LLM applications to production
Multimodal AI expertise practical experience building voice agents, vision systems, or conversational AI serving real users
Strong LLM foundations hands-on with modern foundation models including fine-tuning, prompt engineering, and evaluation methodologies
Agent framework proficiency production experience with LangChain, LlamaIndex, or similar orchestration frameworks
Voice AI platform experience built real-time conversational systems with production STT/TTS integration
Proficiency in Python (production-grade, async programming, type hints) and JavaScript/TypeScript (full-stack development)
RAG implementation experience built retrieval-augmented generation systems with vector databases
MLOps & deployment hands-on with Docker, Kubernetes, CI/CD pipelines, and infrastructure-as-code
Cloud platforms experience with AWS, Azure, or GCP for ML workloads and infrastructure management
Exceptional communication ability to explain complex AI concepts clearly to both technical and business stakeholders
Customer-facing experience in Solutions Architecture, Technical Account Management, or Pre-Sales Engineering is highly desirable
Computer vision experience working with video processing, object detection, or vision-language models is a plus
Model fine-tuning practical experience with LoRA/QLoRA, supervised fine-tuning, or RLHF workflows is a plus
Inference optimization experience with vLLM, TensorRT-LLM, Triton, or model quantization techniques is desirable
Observability tooling practical experience with LLM monitoring, tracing, and evaluation frameworks is a strong plus
Familiarity with WebRTC, real-time streaming protocols, and low-latency media processing

Benefits

Comp & perks

Preferred Attributes:
- Founder-level ownership and bias for action.
- Strong strategic thinking and ability to connect technical decisions to business impact.
- Excellent communication and mentoring skills.
- Thrives in ambiguity, fast-paced environments, and early-stage startup culture.
Why Join aion?
- Work directly with high-pedigree founders shaping technical and product strategy.
- Build infrastructure powering the future of AI compute globally.
- Significant ownership and impact with equity reflective of your contributions.
- Competitive compensation, flexible work options, and wellness benefits