Operations Machine Learning Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Transform machine learning models, analytical prototypes, and AI solutions into scalable workflows ready for production.

• Design, construct, and sustain automated data and model pipelines utilizing Python, AWS, Databricks, or comparable cloud data platforms, Spark, and CI/CD methodologies.

• Create reusable deployment patterns, templates, documentation, and engineering standards.

• Collaborate with teams from Product & Technology, Data Engineering, Cloud Engineering, DevOps, Delivery Platforms, and business operations.

• Establish monitoring frameworks to assess model performance, data quality, drift, reliability, usage, and business impact.

• Support responsible AI and model governance practices, encompassing documentation, auditability, inputs for explainability, validation workflows, and model health assessments.

• Develop feature engineering pipelines, curated data assets, model-serving workflows, and operational data products.

• Identify and rectify issues, defects, or process deficiencies in machine learning pipelines, data workflows, and deployment automation.

• Convert operational business requirements into technical specifications.

• Convey technical concepts to non-technical stakeholders.

• Engage in cross-functional working sessions and offer technical recommendations.

• Facilitate 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 a related quantitative or technical discipline.

• A minimum of 3 years of pertinent experience in machine learning engineering, MLOps, cloud platform engineering, data engineering, software engineering, or similar technical positions.

• Experience in constructing production-grade data or machine learning workflows using Python.

• Strong expertise in cloud data technologies, ideally AWS and Databricks, Spark, or equivalent platforms.

• Familiarity with CI/CD practices, deployment automation, version control, and foundational software engineering principles.

• Understanding of data engineering concepts, including data pipelines, data quality, orchestration, feature engineering, and scalable processing.

• Proven ability to collaborate with data science teams and translate analytical solutions into dependable operational workflows.

• Capability to work autonomously, produce high-quality work, solicit input from others, and contribute to collective standards and best practices.

• Excellent communication skills, including the capacity to clarify technical concepts to business stakeholders and non-technical audiences.

• Availability five days a week during designated working hours.

• Ability to remain seated at a desk or workstation for extended periods, generally 7–8 hours a day.

• Proficient in operating a computer, utilizing phone systems, typing, and working with multiple software programs concurrently.

🏝️ Benefits

• Medical insurance

• Dental insurance

• Vision insurance

• Life insurance

• Disability insurance

• 401(k) match

• Perks supporting employees, their families, and financial well-being

• Opportunities for career development

• Quarterly bonus

• Restricted stock unit grants based on individual performance

• Fully remote work from home or designated location within the U.S.

• No in-office requirements