{"id":4231305,"url":"https://alion.io/job/sd-solutions-saas-e-commerce-client-3-senior-mlops-engineer-data-ml-platform","title":"SaaS e-commerce Client #3 | Senior MLOps Engineer (Data & ML Platform)","company":{"id":4418535,"name":"SD Solutions","domain":"sdsolutions.tech","url":"https://alion.io/company/sdsolutions-3","size_band":"51-200","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Breezy","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Georgia"],"countries":["GE"],"hiring_countries":["GE"],"hiring_countries_total":1,"salary":null,"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Databricks","optional":false},{"name":"Docker","optional":false},{"name":"Embeddings","optional":false},{"name":"Falcon","optional":false},{"name":"GitHub Actions","optional":false},{"name":"Grafana","optional":false},{"name":"Java","optional":false},{"name":"LLM","optional":false},{"name":"Spark","optional":false},{"name":"Amazon S3","optional":true},{"name":"Anomaly Detection","optional":true},{"name":"Apache Kafka","optional":true},{"name":"Feature Store","optional":true},{"name":"IAM","optional":true},{"name":"MLFlow","optional":true},{"name":"Python","optional":true},{"name":"Scala","optional":true},{"name":"Snowflake","optional":true},{"name":"SQL","optional":true},{"name":"Terraform","optional":true}],"status":"live","first_seen_at":"2026-11-13T08:55:53Z","employer_posted_date":"2026-11-13","last_verified_at":"2026-11-13T09:56:51Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"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.\nYou’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.\nSD Solutions is a staffing company operating globally. Contact us to get more details about the benefits we offer.\nResponsibilities:\nWhat you’ll do:\nOwn 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.\nOnboard new data sources: bring in internal databases, external APIs, partner feeds and web data, and match them to Falcon’s own entities.\nUse LLMs inside pipelines: add LLM steps to batch jobs, such as turning text into embeddings and structured attributes.\nKeep training and serving consistent: make sure features match between training and the live inference service, which includes reading its Java code.\nMonitor 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.\nShip 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.\nWork 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.\nRequirements:\n5+ years in data engineering, MLOps or ML platform roles, with pipelines you’ve run in production\nProduction Spark: complex transformations, window functions, large joins, partitioning, and tuning for shuffles and skew. Databricks (jobs, Delta tables) is a big plus.\nProduction Snowflake: SQL, loading and unloading, and cost management\nLarge data volumes: hundreds of millions of rows a month, with incremental loads and backfills that keep run time and cost under control\nStrong Python: clean, tested code; Spark UDFs including pandas UDFs; pandas and PyArrow\nData quality and monitoring: quality checks, drift and anomaly detection, and alerts people can act on\nDeployment: GitHub Actions, Docker, AWS (S3, IAM) and proper secrets handling\nBackend engineering: comfortable working in a service codebase, not only in notebooks and SQL\nAI-first habits: you already use coding agents daily and look for what to automate\nFluent English and based in Georgia\nNice to have:\nMLflow and feature stores\nAirflow or Databricks Workflows\nKafka or Spark Structured Streaming\nTerraform\nDBT\nScala for Spark\nReading Java\nTime-based splits and preventing data leakage in training sets\nAd-tech or e-commerce data experience\nAbout the company:\nNDA 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\nBy applying for this position, you agree to the terms outlined in our Privacy Policy. Please take a moment to review our Privacy Policy https://sd-solutions.breezy.hr/privacy-notice, and make sure you understand its contents. 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