Senior Machine Learning Engineer

Job not on LinkedIn

🔥 4 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 • 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, 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: testing, version control, code review, and CI/CD • Hands-on Docker experience, including Dockerfiles, multi-stage builds, and production container debugging • Solid AWS experience across EC2, ECS, S3, EFS, CloudWatch, and IAM • Experience building automated build, test, and deployment pipelines with GitHub Actions or equivalent • Working knowledge of MongoDB and PostgreSQL, including secure service connections in containerized environments • Experience supporting the ML lifecycle in production, including MLflow or comparable tools, reproducible training pipelines, and model deployment • Experience with modern Python environment and configuration tooling: uv, pydantic, Hydra/OmegaConf • Experience with workflow orchestrators such as SageMaker Pipelines or Prefect • Comfort with TensorFlow, scikit-learn, LightGBM, and geopandas • Exposure to geospatial data or GIS tooling is a plus, not a requirement • Care for cost efficiency, including right-sizing compute and choosing appropriate storage

🏖️ Benefits

• Full-time employment • Fully remote work arrangement • Work with a multi-award-winning AI solution used by water utilities and municipalities worldwide