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Senior Backend Engineer - AI Platform & MLOps

indrive

New
Senior 59,200 EUR/year 🇬🇧 English
Go Python SQL Redis gRPC Kafka RabbitMQ Docker Kubernetes AWS GCP Terraform Terragrunt Prometheus Grafana ELK scikit-learn PyTorch TensorFlow Databricks SageMaker MLflow Airflow

Job description

About the role

inDrive runs many machine learning models across 48 countries and is expanding its ML platform, which ships to Databricks, SageMaker and self-managed GPU inference, with LLM workloads moving into production. This Senior Backend Engineer builds and runs the services and tooling that ML teams depend on, writing production-grade Go and Python and owning them from design to on-call. The role works with data scientists, ML engineers and software and data engineers.

Key responsibilities

  • Design, build and run backend services and internal tooling for the ML platform in Go and Python, owning delivery, monitoring and on-call.
  • Drive technical research and design for new platform features, weighing trade-offs and documenting them.
  • Build and extend deployment tooling and SDKs for ML teams, including serving, autoscaling and data capture.
  • Integrate ML services with the wider backend via HTTP, gRPC, Kafka and RabbitMQ, built for reliability under high load.
  • Support the full ML delivery cycle: CI/CD for models and pipelines, monitoring and model performance metrics.
  • Build observability end to end: metrics, logs, dashboards, tracing, alerting and runbooks.
  • Write infrastructure as code with Terraform and Terragrunt, and take part in code and design reviews, mentoring engineers and reviewing AI-generated changes.

Required profile

  • 5+ years of commercial backend engineering, including high-load systems.
  • Strong Go with advanced features used in production, and solid Python for batch, streaming and async data processing.
  • Strong SQL, including schema design, indexing, query optimisation and scaling approaches such as replication and partitioning.
  • Experience with Docker, CI/CD pipelines and working Kubernetes; familiarity with AWS/GCP core services.
  • Understanding of the ML lifecycle, including concept drift in production.
  • Ability to explain trade-offs clearly to data scientists, product owners and on-call engineers.

Required skills

  • Redis or similar key-value stores
  • HTTP, gRPC, Kafka or RabbitMQ
  • Prometheus, Grafana, ELK or similar observability tools
  • Nice to have: Databricks, SageMaker, Kubeflow, MLflow, Airflow, vLLM, Triton, Langfuse, AI coding agents, IaC tools

What we offer

  • Annual salary starting from 59,200 EUR gross.
  • Mentoring, career consulting and learning programs.
  • Global Talent Exchange Program and company-wide challenges and volunteering.
  • Co-financed language courses and internal speaking clubs.

Questions fréquentes

Le salaire proposé pour ce poste est de 59k EUR par an. Le détail figure dans l'annonce.
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Published 4 hours ago

Expires 1 month from now

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