#jobs #remote
📍 Формат/working arrangement: Remote
✔️ Должность/position: Intermediate Backend Engineer - AI Powered: ModelOps
🏢 Место работы/workplace: GitLab
💸 Заработная плата/salary estimate: $98k-$210k per year
📈 Обязанности/responsibilities:
Develop and maintain CI/CD pipelines for ML model deployment in Ruby environments
Implement and optimize data processing pipelines using Ruby and relevant frameworks
Collaborate with data scientists to productionize ML models efficiently
Design and implement monitoring and alerting systems for ML model performance
Ensure scalability, reliability, and efficiency of ML systems in production
Contribute to the development of internal MLOps tools and libraries in Ruby
Develop features and improvements to the GitLab product in a secure, well-tested, and performant way
Collaborate with Product Management and other stakeholders within Engineering (Frontend, UX, etc.) to maintain a high bar for quality in a fast-paced, iterative environment
Advocate for improvements to product quality, security, and performance
Solve technical problems of moderate scope and complexity
Craft code that meets our internal standards for style, maintainability, and best practices for a high-scale web environment
Conduct Code Review within our Code Review Guidelines and ensure community contributions receive a swift response
Recognize impediments to our efficiency as a team (“technical debt”), propose and implement solutions
Represent GitLab and its values in public communication around specific projects and community contributions
Confidently ship small features and improvements with minimal guidance and support from other team members. Collaborate with the team on larger projects
Participate in Tier 2 or Tier 3 weekday and weekend and occasional night on-call rotations to assist in troubleshooting product operations, security operations, and urgent engineering issues
📌 Требования/requirements:
Professional experience with Ruby on Rails
Experience with MLOps practices and tools (e.g., MLflow, Kubeflow, or similar)
Solid understanding of machine learning concepts and workflows
Familiarity with containerization (Docker) and orchestration (Kubernetes) technologies
Experience with Python ML libraries (scikit-learn, TensorFlow, PyTorch) as plus
Proficiency in the English language, both written and verbal, is sufficient for success in a remote and largely asynchronous work environment.
Demonstrated capacity to clearly and concisely communicate about complex technical, architectural, and/or organizational problems and propose thorough iterative solutions.
Experience with performance and optimization problems and a demonstrated ability to both diagnose and prevent these problems.
Comfort working in a highly agile, intensely iterative software development process.
An inclination towards communication, inclusion, and visibility.
Experience owning a project from concept to production, including proposal, discussion, and execution.
Self-motivated and self-managing, with excellent organizational skills.
Demonstrated ability to work closely with other parts of the organization.
Share our values, and work in accordance with those values.
Ability to thrive in a fully remote organization.
How To Stand Out
Have contributed a merge request to GitLab or an open source project in the ML space
A Masters or PhD in Data Science or similar discipline
Professional Python or Golang experience
✅ Условия/working conditions:
Benefits to support your health, finances, and well-being
All remote, asynchronous work environment
Flexible Paid Time Off
Team Member Resource Groups
Equity Compensation & Employee Stock Purchase Plan
Growth and development budget
Parental leave
Home office support
📢❗️🚨 Контакты для связи/Contact information:
Ссылка на вакансию: здесь.
📍 Формат/working arrangement: Remote
✔️ Должность/position: Intermediate Backend Engineer - AI Powered: ModelOps
🏢 Место работы/workplace: GitLab
💸 Заработная плата/salary estimate: $98k-$210k per year
📈 Обязанности/responsibilities:
Develop and maintain CI/CD pipelines for ML model deployment in Ruby environments
Implement and optimize data processing pipelines using Ruby and relevant frameworks
Collaborate with data scientists to productionize ML models efficiently
Design and implement monitoring and alerting systems for ML model performance
Ensure scalability, reliability, and efficiency of ML systems in production
Contribute to the development of internal MLOps tools and libraries in Ruby
Develop features and improvements to the GitLab product in a secure, well-tested, and performant way
Collaborate with Product Management and other stakeholders within Engineering (Frontend, UX, etc.) to maintain a high bar for quality in a fast-paced, iterative environment
Advocate for improvements to product quality, security, and performance
Solve technical problems of moderate scope and complexity
Craft code that meets our internal standards for style, maintainability, and best practices for a high-scale web environment
Conduct Code Review within our Code Review Guidelines and ensure community contributions receive a swift response
Recognize impediments to our efficiency as a team (“technical debt”), propose and implement solutions
Represent GitLab and its values in public communication around specific projects and community contributions
Confidently ship small features and improvements with minimal guidance and support from other team members. Collaborate with the team on larger projects
Participate in Tier 2 or Tier 3 weekday and weekend and occasional night on-call rotations to assist in troubleshooting product operations, security operations, and urgent engineering issues
📌 Требования/requirements:
Professional experience with Ruby on Rails
Experience with MLOps practices and tools (e.g., MLflow, Kubeflow, or similar)
Solid understanding of machine learning concepts and workflows
Familiarity with containerization (Docker) and orchestration (Kubernetes) technologies
Experience with Python ML libraries (scikit-learn, TensorFlow, PyTorch) as plus
Proficiency in the English language, both written and verbal, is sufficient for success in a remote and largely asynchronous work environment.
Demonstrated capacity to clearly and concisely communicate about complex technical, architectural, and/or organizational problems and propose thorough iterative solutions.
Experience with performance and optimization problems and a demonstrated ability to both diagnose and prevent these problems.
Comfort working in a highly agile, intensely iterative software development process.
An inclination towards communication, inclusion, and visibility.
Experience owning a project from concept to production, including proposal, discussion, and execution.
Self-motivated and self-managing, with excellent organizational skills.
Demonstrated ability to work closely with other parts of the organization.
Share our values, and work in accordance with those values.
Ability to thrive in a fully remote organization.
How To Stand Out
Have contributed a merge request to GitLab or an open source project in the ML space
A Masters or PhD in Data Science or similar discipline
Professional Python or Golang experience
✅ Условия/working conditions:
Benefits to support your health, finances, and well-being
All remote, asynchronous work environment
Flexible Paid Time Off
Team Member Resource Groups
Equity Compensation & Employee Stock Purchase Plan
Growth and development budget
Parental leave
Home office support
📢❗️🚨 Контакты для связи/Contact information:
Ссылка на вакансию: здесь.