PAR Technology
PAR Technology
PAR Technology мейрамханаларға, қонақжайлылық саласындағы кәсіпорындарға және қызмет көрсету көлемі жоғары басқа да ортаға арналған технологиялар әзірлейді. Оның платформасы сату орындарындағы жүйелерді, цифрлық тапсырыс беруді, төлемдерді және клиенттердің адалдығын арттыру құралдарын біріктіріп, операторларға залдағы және асүйдегі жұмыс үдерістерін үйлестіруге көмектеседі. PAR Technology жылдам қызмет көрсететін және fast-casual мейрамханаларға, кинотеатрларға, казиноларға, тақырыптық саябақтарға, қонақүйлерге және шағын дүкендерге қызмет көрсетеді. Бұлтқа негізделген өнімдері операцияларды бірқалыпты жүргізуге және қонақтарға көрсетілетін қызметтің тұрақты болуына мүмкіндік береді.

MLOps Engineer, Identity Resolution

Bring Bridg’s identity-resolution models into production for PAR Technology’s restaurant software platform. Build AWS and Spark pipelines, CI/CD, monitoring, and agent-queryable data interfaces.

Сипаттама

  • Move Bridg’s identity-resolution model from notebooks into monitored, automated production.
  • Build and maintain reliable, scalable data and machine learning pipelines.
  • Write tests and add observability for match data.
  • Optimize Spark jobs and build CI/CD workflows.
  • Strengthen system testing and documentation.
  • Work with data science to deliver production machine learning systems.
  • Conduct exploratory data analysis and investigate data quality.
  • Maintain feature pipelines and consistency between model training and serving.
  • Evaluate champion and challenger models and flag anomalous results.
  • Create lightweight interfaces that let agent workflows query identity-resolution outputs.
  • Use AI for coding, refactoring, infrastructure as code, design documentation, log and run summaries, dataset exploration, and evaluation-case generation.
  • Report to Bridg’s Director of Product.

Талаптар

  • 2–4 years of experience building production data or machine learning systems.
  • Bachelor’s degree in computer science, data engineering, or a related field, or equivalent practical experience.
  • Experience building and maintaining automated, tested machine learning or data pipelines.
  • Experience improving CI/CD for data or machine learning workflows, including Git-based processes, automated unit and integration tests, and branch-based promotion through development, staging, and production.
  • Experience with workflow orchestration tools such as Airflow, Step Functions, or Databricks Workflows, including retries, backfills, SLA monitoring, and alerting.
  • Familiarity with experiment tracking and model registries such as MLflow.
  • Exposure to monitoring and observability, data-quality and schema-drift checks, and input and output distribution drift.
  • Experience with infrastructure as code, secrets management, and reproducible Python environments.
  • Production experience with AWS services including S3, EMR, Glue, Step Functions, Lambda, IAM, and CloudWatch.
  • Working knowledge of Spark performance topics including skew, shuffle, spill, partitioning, and join strategies.
  • Experience serving processed outputs to downstream systems such as Redshift.
  • Ability to conduct exploratory data analysis and data-quality investigations.
  • Experience building and maintaining feature pipelines and keeping training and serving consistent.
  • Foundation in applied statistics, including probability, hypothesis testing, sampling, and evaluation metrics.
  • Fluency with the Python data science stack, including pandas, scikit-learn, and PySpark.
  • Interest in LLM-based agent data integration and willingness to build interfaces such as MCP servers, REST or GraphQL endpoints, or structured feeds.
  • Good judgment when working with data contracts.
  • Comfort working with datasets that contain personally identifiable information.
  • Daily use of AI coding assistants, with accountability for reviewing and testing AI-generated code.
  • Must be legally authorized to work in the United States or Canada.
  • Must not have a restrictive covenant agreement that prevents employment at PAR.

Артықшылықтар

  • Eligibility for a bonus.
  • Potential additional compensation, including commission and/or equity, as applicable.
  • Remote work arrangement in eligible locations.
  • Reasonable accommodations for individuals with disabilities.

Ұқсас жұмыс орындары

Alliant Insurance Services

Divisional AI Engineer III

Alliant Insurance Services

Lead the architecture and reliability of shared LLM infrastructure, while driving adoption across products. Build reusable orchestration, observability, and production services.

Ашу
CDW
Volga Partners

Remote Data Annotation Specialist, Object Detection — United States

Volga Partners

Annotate visual datasets for Volga Partners’ AI projects, labeling objects to support computer vision systems. Help improve object detection quality through careful, consistent work.

Ашу
KeyrusCloud

Forward Deployed AI Engineer

KeyrusCloud
11 – 50 Қызметкерлер
SaaSКәсіпорынКонсалтинг

Deploy production AI solutions for Keyrus, an enterprise intelligence consultancy. Connect APIs, cloud platforms, enterprise systems, and client workflows.

Ашу
Netflix

Senior Software Engineer, AI Platform Model Development

Netflix

Build Netflix’s AI Platform to support machine learning model development, experimentation, and deployment. Partner with researchers and data scientists to improve tools across the machine learning lifecycle.

Ашу