Senior MLOps Engineer

EPAM Systems; Colombia; Remote; COP 144,000,000 - 216,000,000; Full time

Benefits offered by this job

Healthcare benefits

Paid time off

Upskilling and certifications

Global career opportunities

Volunteer opportunities

Job summary

EPAM Systems, Inc. seeks a Senior MLOps Engineer to build a test intelligence platform for two game franchises, ensuring full re-derivability and replayable configurations from day one.

You will own signal catalogue operations, vector index versioning, and the calibration harness while maintaining strong model lineage and reproducibility across deployments. You will collaborate with AI developers and data engineers, implement monitoring for data health and run behavior, and drive experimentation

Qualifications

• 3+ years of experience in MLOps or ML platform engineering.
• Strong ML model lifecycle management, including versioning and rollback.
• Background in signal computation pipelines, provenance, and grain translation.
• Proficiency in Python and SQL for ML pipeline automation.
• Experience with model monitoring and drift detection.

Responsibilities

• Own Signal Catalogue operations: refresh, translation, provenance across signals.
• Coordinate Semantic Vector Index versioning with AI team and manage reindexing when models change.
• Design and run Back-test & Calibration Harness with as-of filtering and replay.
• Enforce holdout and configuration sweeps; publish winning configurations.
• Lead Model Generation & Experimentation for scoring configurations and routes.
• Maintain model lineage across configurations for both franchises.
• Implement MLOps Monitor and Data-Health Monitor across ingestion channels.
• Support exploration cadence with provenance to avoid bias in recommendations.
• Contribute to operator runbooks covering signal refresh, calibrations, and reindex procedures.

Skills

MLOps

Python

SQL

Data pipelines

Model monitoring

Experiment tracking

Education

Bachelor's in CS/Engineering

Tools

Kubeflow

MLflow

Snowflake ML

pgvector

Job description

We are seeking a Senior MLOps Engineer to join an MVP engagement with a major AAA game publisher, building a test intelligence platform for two game franchises in parallel. A core design principle is full re-derivability and model lineage from day one — every run must be replayable from its stored configuration version and feed read positions. The signal catalog feeds a scoring strategy engine with versioned configurations, and calibration sweeps over historical data produce suggested weight updates surfaced directly in the Settings View.This role ensures the ML and signal components are production-ready, reproducible, and improvable over time, forming the foundation of the system's long-term value as franchise history accumulates and models are refined.ResponsibilitiesOwn Signal Catalogue operations: signal refresh orchestration triggered by feed read-position advances, grain translation between per-test, per-area, and per-run signal families, and provenance capture across all 8 signalsOperate the Semantic Vector Index versioning: coordinate with the Senior AI Developer on model and dimension stamp conventions; design and execute the controlled reindex path when the enterprise AI gateway model changesDesign, implement, and own the Back-test & Calibration Harness: as-of temporal filtering across all record families, replay runner, look-ahead spot audit, and configuration sweep runnerEnforce holdout patch-set discipline, configuration sweep over route limits, thresholds, weights, and Composition setting; produce catch-rate vs. scope tables per candidate configuration and publish winning configurations as suggested-weight proposals into the Settings ViewLead Model Generation & Experimentation: systematic experimentation framework over scoring strategy configurations, tracking which signal weights and route combinations yield the best catch-rate vs. scope trade-offMaintain model lineage across configuration versions for both franchisesImplement the MLOps Monitor and Data-Health Monitor: catch-rate floor monitoring, run-behaviour drift counters (per-run candidate volumes per route, score distribution vs. usual range), data-health telemetry across all ingestion channelsManage exploration cadence support: unbiased random-sample injection with provenance ensuring exploration entries are never counted as model recommendationsContribute to operator runbook sections covering signal refresh, calibration campaigns, model generation runs, and embedding reindex proceduresRequirements3+ years of experience in MLOps or ML platform engineeringExpertise in ML model lifecycle management, including versioning, configuration management, and rollbackBackground in signal computation pipeline design, covering scheduled refresh, provenance capture, and grain translationProficiency in calibration methodology: holdout discipline, configuration sweep design, and catch-rate vs. scope measurementKnowledge of as-of temporal data systems or back-test harness design and operationSkills in Python and SQL for ML pipeline automationCompetency in model monitoring, including drift detection, catch-rate floor monitoring, and run-behavior drift countersCapability to collaborate with data engineers and AI developers on feature alignmentQualifications in documenting calibration procedures, signal definitions, and operational runbooksFamiliarity with Spec Driven DevelopmentEnglish proficiency at an Upper-Intermediate level (B2) or higherNice to haveUnderstanding of MLflow, Kubeflow, or equivalent experiment tracking platformsFamiliarity with Snowflake ML or SnowparkShowcase of embedding model versioning and controlled reindex orchestrationSkills in pgvector or vector store operational managementBackground in gaming domain or QA toolingWe offerInternational projects with top brandsWork with global teams of highly skilled, diverse peersHealthcare benefitsEmployee financial programsPaid time off and sick leaveUpskilling, reskilling and certification coursesUnlimited access to the LinkedIn Learning library and 22,000+ coursesGlobal career opportunitiesVolunteer and community involvement opportunitiesEPAM Employee GroupsAward-winning culture recognized by Glassdoor, Newsweek and LinkedInEPAM is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, sexual orientation, gender identity or expression, disability, protected veteran status, or any other characteristic protected by applicable law.