Senior MLOps Engineer

🔥 0 minutes ago

🇬🇷 Greece – 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.

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VODA.ai®

WebsiteLinkedInAll Job Openings

11 - 50 employees

Founded 2017

🤖 Artificial Intelligence

☁️ SaaS

🤝 B2B

💰 $10M Series A - VODA.ai on 2025-06

Artificial Intelligence • SaaS • B2B

VODA. ai is a company that provides an AI-driven decision-support platform for water utilities, helping them plan operations, detect weak and leaky pipes, reduce water loss, and prevent catastrophic failures. Founded in 2017, VODA. ai uses predictive analytics and domain expertise to analyze infrastructure data (over 1M miles of pipe across multiple countries and states) and deliver actionable insights to utility engineers and asset managers. The company operates as a B2B SaaS provider focused on simplifying engineering for water professionals and improving customer outcomes.

📋 Description

• Own the reliability, scalability, and automation of machine-learning pipelines • Manage both infrastructure and the machine-learning lifecycle • Containerize pipeline services with Docker and deploy them on AWS • Design scalable, event-driven execution for data preparation, model training, and prediction jobs • Build and harden CI/CD pipelines in GitHub Actions • Improve observability through logging, metrics, and alerting • Strengthen the model lifecycle through reproducible training environments, experiment tracking with MLflow, model versioning, and deployment • Evolve and scale production pipelines serving customers • Design cloud architecture and drive platform modernization from proposal to production • Own initiatives end-to-end and ship incrementally without disrupting live systems • Partner with data scientists and DevOps engineers across the stack • Improve training, evaluation, and deployment workflows

🎯 Requirements

• 5+ years of experience running production Python systems • Strong software engineering fundamentals, including testing, version control, code review, and CI/CD • Hands-on Docker experience, including writing and optimizing Dockerfiles, multi-stage builds, and debugging containers in production • Solid cloud experience across compute and storage • Experience with AWS EC2, ECS, S3, EFS, CloudWatch, and IAM • Experience building automated build, test, and deployment pipelines with GitHub Actions or equivalent • Working knowledge of document and relational databases, including MongoDB and PostgreSQL • Ability to connect services securely to databases in containerized environments • Experience supporting the ML lifecycle in production, including experiment tracking and model management with MLflow or a comparable tool • Experience with reproducible training pipelines and model deployment • Experience with modern Python environment and configuration tooling, including uv, pydantic, and Hydra/OmegaConf • Experience with workflow orchestrators such as SageMaker Pipelines or Prefect • Comfort working with TensorFlow, scikit-learn, LightGBM, and geopandas • Exposure to geospatial data or GIS tooling such as geopandas, PostGIS, or ArcGIS is a plus, not a requirement • Care about cost efficiency, including right-sizing compute and choosing appropriate storage

🏖️ Benefits

• Full-time employment • Fully remote work arrangement • Opportunity to work on AI-based infrastructure supporting water utilities and municipalities • Collaboration with data scientists and DevOps engineers across the stack • Work on a multi-award-winning solution with customers worldwide