Jobs

Location

Our team is fully remote and is made up of leaders, creators, visionaries, parents, partners, cycling enthusiasts, winemakers, and champion jugglers (yes, really!) living and working all around the world. This position is open to candidates in South America.

Job Description

Reporting directly to the Director of Engineering while collaborating closely with the Head of Data Science, the Backend / MLOps Engineer will serve as a critical component of our technological ecosystem. This role will involve extensive work in Python and PHP to implement, deploy, and maintain machine learning models, APIs, and data pipelines. The candidate should be well-versed in both languages and should exemplify exceptional coding standards, innovative thinking, and a dedication to scalability and system reliability.

Key Responsibilities

• Machine Learning Operations (MLOps)
  • Work with the data science team to deploy machine learning and large language models into production environments, ensuring high performance, availability, and resource efficiency.
  • Collaborate with engineering and data science teams to establish and enforce model governance protocols, including versioning, monitoring, and rollback strategies.
• Data Pipeline Architecture
  • Develop, maintain, and scale data pipelines using Python to ingest, transform, and deliver large datasets for downstream applications.
  • Coordinate with the engineering and data teams to enforce best practices in data lineage, governance, and metadata management.
• API and Service Development
  • Engineer RESTful APIs and backend services in PHP and/or Python, adhering to the highest security and performance standards.
  • Implement API documentation, versioning, and rate-limiting to facilitate both internal and third-party integrations.
• System Scalability and Reliability
  • Engage in system architecture planning sessions with the engineering team to ensure scalability, fault tolerance, and high availability of all system components.
  • Participate in cloud resource allocation and cost optimization decisions, working across AWS and Azure platforms.
• Quality Assurance and Code Review
  • Implement rigorous automated testing protocols for unit, integration, and end-to-end tests to maintain code quality and system reliability.
  • Contribute to peer code review processes, adhering to the engineering team’s high standards for code quality and maintainability.
• Strategic Collaboration
  • Serve as a liaison between engineering and data science teams, ensuring that machine learning models and data pipelines are aligned with the overarching technology strategy.
  • Provide technical insights and recommendations for future growth, keeping an eye on emerging technologies and methodologies that could benefit the organization.

Required Skills and Experience

• Bachelor’s or higher degree in Computer Science, Engineering, or a related field.
• Proficiency in Python and PHP is mandatory.
• Demonstrable experience in deploying and maintaining machine learning models.
• Mastery over MLOps tools such as MLflow, Kubernetes, and Docker.
• Solid understanding of RESTful API development in PHP, including advanced security protocols.
• Previous experience with cloud platforms and services such as AWS and Azure.
• Unparalleled problem-solving skills and a proactive mindset.

Preferred Skills and Experience

• Knowledge of optimization algorithms.
• Experience with real-time data processing frameworks like Kafka, Flink, or Storm.
• Experience serving LLMs in production environments.
• Contributions to open-source projects related to MLOps or back-end engineering.