Senior I ML/CV Engineer

Established in 1997, Softeq was built from the ground up to specialize in new product development and R&D, tackling the most difficult problems in the tech sphere. Now we've expanded to offer early-stage innovation and ideation plus digital transformation business consulting. Our superpower is to deliver all of this under one roof on a global scale. So let's get started and build a better future together!

As we're expecting to expand our team and launch new projects within the next 1-2 months, we're already accepting applications and starting the interview process for selected candidates. We'd love to hear from you - feel free to apply!

What the role does here

• Moves predictive models from experiment into regular operation: delay and duration forecasting, congestion forecasting, cost estimation, anomaly detection;
• Builds and maintains feature pipelines over the curated data layer, with a documented catalog of model inputs and their lineage;
• Makes training sets reproducible through table versioning and access to historical data states.
• Runs batch and near-real-time inference as platform jobs wired into the existing dependencies and schedules;
• Publishes models as endpoints for the application to consume, and watches latency and cost per call;
• Owns release discipline: versioning, retraining, rollback, promotion of models across environments;
• Provides quality monitoring, drift detection on inputs and outputs, input validation and explainability support.

Must have

• Production-grade Python and PySpark, and confident Spark SQL;
• Databricks at development and operations depth: jobs and orchestration with dependencies, job clusters and cluster policies, portable project bundles, source control integration;
• Unity Catalog: grants on tables and models, lineage, environment separation through catalogs;
• Working Delta Lake knowledge: table versions and time travel, change data feed, optimization, and how data layout affects feature read performance;
• MLflow: experiment tracking, model registry, version promotion, publishing models as endpoints;
• Feature storage and reuse, with consistent computation between training and inference;
• Hands-on experience operating models in production: monitoring, drift, retraining, incidents, rollback;
• Time-series and forecasting methods;
• Git, CI/CD, containers, secure handling of secrets.

Nice to have

• Built-in platform monitoring for data and model quality;
• Production ML on Azure and integration with cloud services;
• Understanding of the platform consumption model and cost tuning for recurring jobs;
• Geospatial features and route data;
• Environments where a model must be explainable to business owners and auditors;
• Transportation, logistics or supply chain.

Softeq communicates only from @softeq.com email addresses. We never request payments or fees for any reason during hiring - including trainings or courses to be completed, equipment, onboarding, or background checks - and we will not ask for banking information, cryptocurrency or gift cards. If you receive a message from any other domain or requesting payment, do not respond and report it to [email protected]