Senior Forward Deployed ML Engineer, Agents at AION | England, GB | Rezi

Senior Forward Deployed ML Engineer, Agents at AION

Senior Forward Deployed ML Engineer, Agents

AION · England, GB

1 months ago

Senior Forward Deployed ML Engineer, Agents

AION · England, GB

2 months ago
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About the Role

aion is the Enterprise AI Platform, a full-stack solution for building, fine-tuning, deploying, and forward-deploying AI for enterprises at scale. We are looking for exceptional people to help us scale.

Responsibilities

  • 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 frameworks like LangChain or LlamaIndex
  • 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 and online monitoring

Requirements

  • 3-5+ years of experience building production-grade multimodal AI systems and LLM applications
  • Comfortable writing production code, presenting technical solutions to C-level executives, and debugging complex AI systems
  • Shipped voice agents, video processing systems, or conversational AI to production
  • Comfortable working across the full AI deployment lifecycle from use case discovery and solution architecture to multimodal agent development, MLOps pipeline implementation, and production optimization
  • Understand what makes agents perform well in production and how to systematically improve quality through observability and evaluation
  • Experience with voice AI platforms, RAG systems, and LLM orchestration frameworks is highly desirable
  • Exceptional communication skills, customer empathy, and the drive to build AI solutions that transform enterprise operations globally
  • 6-8+ years of hands-on experience building production AI/ML systems, with 3-4+ 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
  • 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

Skills

  • Multimodal AI
  • LLM applications
  • Voice agents
  • Video processing
  • Conversational AI
  • STT APIs
  • TTS APIs
  • LLMs
  • Computer vision
  • LangChain
  • LlamaIndex
  • Python
  • TypeScript
  • REST APIs
  • GraphQL APIs
  • WebSocket APIs
  • RAG systems
  • Vector databases
  • Docker
  • Kubernetes
  • CI/CD pipelines
  • Infrastructure-as-code
  • AWS
  • Azure
  • GCP
  • WebRTC
  • Real-time streaming protocols
  • Low-latency media processing

Experience Level

  • 3-5+ years of experience
  • 6-8+ years of hands-on experience
  • 3-4+ years deploying LLM applications to production

Benefits

  • Competitive compensation
  • Flexible work options
  • Wellness benefits
  • Significant ownership and impact with equity reflective of your contributions

About the Company

  • aion is the Enterprise AI Platform, a full-stack solution for building, fine-tuning, deploying, and forward-deploying AI for enterprises at scale.
  • By abstracting away infrastructure complexity, aion unifies compute orchestration, training workflows, data pipelines, model versioning, and deployment into a streamlined enterprise experience.
  • We forward-deploy AI for enterprises, enabling organizations to rapidly implement production-ready AI solutions.
  • We're a fast-growing, VC-backed startup led by founders with a track record of successful exits.
  • With teams across the US, UK, and India, we're building the next generation of enterprise AI infrastructure and are looking for exceptional people to help us scale.