Top Tech Jobs & Startup Jobs

Manage end-to-end technical recruitment for Data & AI roles: partner with hiring managers, source candidates, run interviews, track recruiting metrics, and optimize hiring pipelines while ensuring a strong candidate experience.

Design, build, and operate production data pipelines and dbt models to serve ML and analytics workflows. Work with relational, vector, and graph stores, large-scale Spark/PySpark processing, SQL transformations, Python ETL, and ensure data quality via tests, monitoring, logging, and CI/CD. Collaborate with data scientists and maintain infrastructure-as-code for reliable, production-grade data platforms.

Design, build, and operate production-scale data pipelines and multi-model data platforms (relational, vector, graph) to serve AI/BI systems. Own architecture, reliability, observability, and mentoring; implement ETL/ELT with Spark, dbt, cloud infrastructure, CI/CD, and IaC.

Support design and development of ETL pipelines, assist with data migrations and cloud transitions, troubleshoot data processes, and collaborate with architects, developers, and analysts while learning cloud and data engineering tools.

As a Senior MLOps Engineer, you will build and maintain infrastructure for deploying ML models, create automated ML pipelines, ensure system reliability, and enhance collaboration across AI teams.

Execute end-to-end CRM campaigns: audience selection, offer design, execution, monitoring and reporting. Analyze customer data, build segmentation models (primarily using IBM SPSS Modeller), track campaign KPIs, and translate insights into decision-ready summaries while partnering with cross-functional teams.

The Engineering Manager will lead technical teams in data and AI projects, ensuring high standards in delivery, manage senior engineers, foster collaboration, and drive improvements in engineering practices.