Machine Learning Ops Engineer

🔥 0 minutes ago

⛰️ Colorado, Florida, +6 more states – Remote

⛰️ Colorado – Remote 🐊 Florida – Remote 🌽 Illinois – Remote 🗽 New York – Remote 🌲 North Carolina – Remote ❄️ Minnesota – Remote 🔔 Pennsylvania – Remote 🤠 Texas – Remote

💵 $125k - $160k / year

⏰ Full Time

🟢 Junior

🟡 Mid-level

🤖 Machine Learning Engineer

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PAR Technology

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1982

🍽️ Food & Beverage

💼 Consulting

📦 Logistics

Food & Beverage • Consulting • Logistics

PAR Technology is a company that provides a comprehensive suite of technology solutions aimed at the restaurant and hospitality industries. Their offerings include point of sale (POS) systems, digital ordering platforms, payment services, and customer loyalty solutions. PAR Technology aims to streamline restaurant operations through cloud-based technologies that improve speed of service, reduce wait times, and enhance the overall guest experience. They cater to various settings such as quick service, fast-casual, cinemas, casinos, theme parks, hospitality establishments, and convenience stores. By integrating various processes from front of house to back of house, PAR Technology supports a unified commerce experience for enterprises and businesses aspiring for growth.

📋 Description

• Take Bridg’s identity resolution model from notebooks to monitored, automated production • Build and maintain reliable, scalable data and ML pipelines • Write tests and implement observability for match data • Tune Spark jobs and build CI/CD workflows • Improve system testing and documentation • Partner with data science on production ML systems • Run exploratory data analysis and data-quality investigations • Maintain feature pipelines and consistency between training and serving • Evaluate champion/challenger models and identify anomalous results • Build lightweight interfaces to make identity-resolution outputs queryable by agent workflows • Apply AI to coding, refactoring, infrastructure as code, design documentation, log/run summarization, dataset exploration, and evaluation-case generation • Report to the Director of Product, Bridg

🎯 Requirements

• 2–4 years of experience building production data or ML systems • Bachelor’s degree in Computer Science, Data Engineering, or a related field, or equivalent practical experience • Experience building and maintaining automated, tested ML or data pipelines • Experience optimizing CI/CD for data/ML, including Git-based workflows, automated unit and integration tests, and branch-based promotion through dev/stage/prod • Experience with workflow orchestration using 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/output distribution drift • Experience with infrastructure as code, secrets management, and reproducible Python environments • Production experience on AWS, including S3, EMR, Glue, Step Functions, Lambda, IAM, and CloudWatch • Working knowledge of Spark performance, including skew, shuffle, spill, partitioning, and join strategies • Experience serving processed outputs to downstream systems such as Redshift • Ability to run EDA and data-quality investigations • Experience building and maintaining feature pipelines and keeping training and serving consistent • Applied statistics foundation in probability, hypothesis testing, sampling, and evaluation metrics • Fluency across 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/GraphQL endpoints, or structured feeds • Good judgment about data contracts • Comfort working with PII-bearing datasets • Daily use of AI coding assistants and accountability for reviewing and testing AI-generated code • Must be legally authorized to work in the U.S. or Canada • No restrictive covenant agreement preventing employment at PAR

🏖️ Benefits

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