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Machine Learning Engineer
Machine Learning EngineerAvensys Consulting • Paris, Île-de-France, France
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Machine Learning Engineer

Machine Learning Engineer

Avensys Consulting • Paris, Île-de-France, France
Il y a 4 jours
Type de contrat
  • Temps plein
Description de poste

We are seeking a highly experienced Senior Forward Deployment Engineer to lead the technical implementation, integration, and production rollout of advanced Agentic AI platforms in large-scale enterprise environments. This role combines deep engineering expertise, strong DevOps capabilities, and hands-on ML operationalization skills to ensure seamless deployment, scalability, and reliability of AI-driven systems.

This is a senior engineering position requiring ownership, architectural thinking, and the ability to collaborate directly with enterprise technical teams, product engineering, and leadership stakeholders.

Key Responsibilities

1. Deployment Engineering

  • Lead the end-to-end technical deployment of the Agentic AI platform across complex enterprise environments.
  • Architect, design, and build integration pipelines connecting customer systems, APIs, databases, and enterprise applications.
  • Deploy, operate, and scale machine learning models in production with a focus on performance, reliability, and monitoring.
  • Automate end-to-end deployments using CI / CD pipelines , infrastructure-as-code , and container orchestration tools (Docker, Kubernetes).
  • Ensure smooth rollout, versioning, and updates across staging, pre-prod, and production environments.

2. AI Platform Integration & Optimization

  • Implement and customize platform components, SDKs, APIs, extensions, and microservices to meet customer-specific use cases.
  • Build tools and automation scripts for data preprocessing , feature engineering , batch / real-time inference , and model lifecycle operations.
  • Optimize model serving layers for low latency , high throughput , and efficient resource utilization .
  • Improve caching, load balancing, and inference pipelines to support mission-critical AI workloads.
  • 3. Reliability, Security & Compliance

  • Architect deployment solutions aligned with enterprise-grade reliability, resilience, and observability standards.
  • Implement best practices for security , including encryption, IAM, secret management, and network policies.
  • Ensure platform deployments comply with SOC2, HIPAA, GDPR , and industry-specific regulatory requirements.
  • Set up robust monitoring, logging, and alerting frameworks for proactive issue resolution.
  • 4. Engineering Leadership & Technical Escalation

  • Act as the senior technical lead on customer deployments, owning resolution of complex engineering challenges.
  • Work directly with customer engineering, infrastructure, and architecture teams to embed the platform into core production workflows.
  • Provide critical field insights and feedback to the product engineering team for continuous platform improvement.
  • Lead deep-dive technical investigations, post-mortems, performance tuning, and scalability assessments.
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