[Hiring] Senior MLOps Engineer @SD Solutions

Role Description

On behalf of NDA, SaaS e-commerce, SD Solutions is looking for a talented Senior MLOps Engineer (Data & ML Platform) based in Georgia (Tbilisi) to join our growing team. You'll own the data that Falcon's offer-ranking model learns from: the raw sources, the pipelines, the training tables, and the monitoring around them.

Responsibilities:

• Own the ML data pipelines:
  • Build and run batch pipelines on Spark and Databricks, from raw data to feature and training tables, including enrichment and backfills for late-arriving data.
• Onboard new data sources:
  • Bring in internal databases, external APIs, partner feeds and web data, and match them to Falcon's own entities.
• Use LLMs inside pipelines:
  • Add LLM steps to batch jobs, such as turning text into embeddings and structured attributes.
• Keep training and serving consistent:
  • Make sure features match between training and the live inference service, which includes reading its Java code.
• Monitor data and model inputs:
  • Run scheduled data quality checks and Grafana alerts that catch bad data before it reaches the model, and find the root cause when something breaks.
• Ship like an MLOps engineer:
  • Deploy pipelines through CI/CD (GitHub Actions, Docker, AWS) with proper secrets handling, and keep run time and cost under control.
• Work with AI agents:
  • Coding agents write most of Falcon's code. You'll decide where agents fit, then check their output on row counts, distributions and edge cases before anyone relies on it.

Qualifications

• 5+ years in data engineering, MLOps or ML platform roles, with pipelines you've run in production.
• Production Spark: complex transformations, window functions, large joins, partitioning, and tuning for shuffles and skew. Databricks (jobs, Delta tables) is a big plus.
• Production Snowflake: SQL, loading and unloading, and cost management.
• Large data volumes: hundreds of millions of rows a month, with incremental loads and backfills that keep run time and cost under control.
• Strong Python: clean, tested code; Spark UDFs including pandas UDFs; pandas and PyArrow.
• Data quality and monitoring: quality checks, drift and anomaly detection, and alerts people can act on.
• Deployment: GitHub Actions, Docker, AWS (S3, IAM) and proper secrets handling.
• Backend engineering: comfortable working in a service codebase, not only in notebooks and SQL.
• AI-first habits: you already use coding agents daily and look for what to automate.
• Fluent English and based in Georgia.

Requirements

• Nice to have:
  • MLflow and feature stores.
  • Airflow or Databricks Workflows.
  • Kafka or Spark Structured Streaming.
  • Terraform.
  • DBT.
  • Scala for Spark.
  • Reading Java.
  • Time-based splits and preventing data leakage in training sets.
  • Ad-tech or e-commerce data experience.

Company Description

NDA helps eCommerce brands boost revenue with highly relevant and rewarding post-purchase offers. Our platform delivers personalized offers to customers right after checkout, driving repeat purchases and increasing lifetime value through seamless integrations and data-driven insights.

By applying for this position, you agree to the terms outlined in our Privacy Policy. Please take a moment to review our Privacy Policy here , and make sure you understand its contents. If you have any questions or concerns regarding our Privacy Policy, please feel free to contact us.