Senior ML Engineer / Data Scientist

On-siteJust posted

Design and develop a self-learning Postlog and Prelog recognition system using modern ML and LLM techniques
Build and maintain versioned prompts, evaluation datasets, and few-shot exemplars
Apply production-grade LLM practices including schema-constrained extraction, grounding strategies, and low-confidence fallback handling
Improve recognition quality and optimize layout and header mapping performance
Analyze production failures and enhance prompts, retrieval pipelines, and model behavior
Run evaluation pipelines and shadow-mode comparisons against legacy systems and gold datasets
Monitor confidence scores, latency, operational quality, and infrastructure costs
Develop entity-matching systems for Station, Advertiser, and CreativeID master data
Implement confidence scoring, thresholding, and auditability mechanisms
Transform human and machine corrections into labeled signals for continuous model improvement
Monitor prompt and model drift in production environments
Collaborate with Data Engineering teams on ML integration and operationalization
Communicate technical findings and recommendations to engineering teams and Customer stakeholders

At least 5 years of experience in Machine Learning, Data Science, or ML Engineering
Proven experience delivering ML models or LLM-powered systems into production
Strong hands-on experience with Large Language Models in real products or pipelines
Deep understanding of prompt engineering, prompt versioning, evaluation methodologies, and grounding strategies
Experience handling low-confidence scenarios and optimizing cost and latency for LLM systems
Strong Python and SQL skills
Solid knowledge of statistics, confidence estimation, sampling, hypothesis testing, and threshold optimization
Experience with classification, ranking, matching, or recommendation-related problems
Understanding of offline evaluation metrics, holdout validation, and production monitoring
Hands-on experience with AWS cloud services including S3, IAM, CloudWatch, and orchestration services
Strong communication and collaboration skills
Upper-Intermediate English level or higher

WILL BE A PLUS

LLM-related certifications
Experience with Amazon Bedrock or equivalent enterprise LLM platforms
Production experience with Claude/Sonnet-class models
Experience with Excel or layout extraction systems
Knowledge of confidence calibration, active learning, or weak supervision techniques
Experience with cost-aware LLM operations including caching, routing, and fallback models
Advertising or media domain knowledge
Familiarity with Glue, Airflow, or similar orchestration and data pipeline tools