Operations Machine Learning Engineer

🔥 3 minutes ago

🇺🇸 United States – Remote

💵 $140k - $163k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

👻 Ghost score 0%

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Paylocity

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 1997

👥 HR Tech

☁️ SaaS

🤝 B2B

💰 $10M Venture Round - Paylocity on 2008-05

HR Tech • SaaS • B2B

Paylocity is a provider of cloud-based payroll and human capital management software for businesses of all sizes. Its platform includes payroll, HR, time & labor, benefits administration, talent management (recruiting, onboarding, performance, learning), employee experience tools and AI-driven features, and it serves small businesses through enterprises as well as partners such as accountants, brokers, and tech partners.

📋 Description

• Convert machine learning models, analytical prototypes, and AI solutions into scalable production-ready workflows • Design, build, and maintain automated data and model pipelines using Python, AWS, Databricks or similar cloud data platforms, Spark, and CI/CD practices • Develop reusable deployment patterns, templates, documentation, and engineering standards • Collaborate with Product & Technology, Data Engineering, Cloud Engineering, DevOps, Delivery Platforms, and business operations teams • Create monitoring frameworks for model performance, data quality, drift, reliability, usage, and business impact • Support responsible AI and model governance practices, including documentation, auditability, explainability inputs, validation workflows, and model health checks • Develop feature engineering pipelines, curated data assets, model-serving workflows, and operational data products • Identify and resolve issues, defects, or process gaps in machine learning pipelines, data workflows, and deployment automation • Translate operational business needs into technical requirements • Communicate technical concepts to non-technical stakeholders • Participate in cross-functional working sessions and provide technical recommendations • Help drive project execution across Data Science, business, and technology teams

🎯 Requirements

• Bachelor's degree in computer science, data engineering, machine learning engineering, engineering, statistics, mathematics, data science, or another quantitative or technical field • At least 3 years of relevant experience in machine learning engineering, MLOps, cloud platform engineering, data engineering, software engineering, or similar technical roles • Experience building production-grade data or machine learning workflows in Python • Strong background with cloud data technologies, preferably AWS and Databricks, Spark, or similar platforms • Experience with CI/CD practices, deployment automation, version control, and software engineering fundamentals • Knowledge of data engineering concepts, including data pipelines, data quality, orchestration, feature engineering, and scalable processing • Demonstrated ability to partner with data science teams and translate analytical solutions into reliable operational workflows • Ability to work independently, deliver high-quality work, seek input from others, and contribute to shared standards and best practices • Strong communication skills, including the ability to explain technical concepts to business stakeholders and non-technical audiences • Availability five days per week during designated work hours • Ability to sit at a desk or workstation for extended periods, typically 7–8 hours a day • Ability to operate a computer, use phone systems, type, and use multiple software programs simultaneously

🏖️ Benefits

• Medical insurance • Dental insurance • Vision insurance • Life insurance • Disability insurance • 401(k) match • Perks supporting employees, their families, and finances • Career development opportunities • Quarterly bonus • Restricted stock unit grant based on individual performance • Fully remote work from home or location of record within the U.S. • No in-office requirements