ModelOps Automation Developer

ModelOps Automation Developer

Location: Remote in LATAM

Position Overview

We are seeking a ModelOps Automation Developer to design and build software solutions that support AI enablement and automate the machine learning model lifecycle. This role focuses on Python development within Databricks, creating reusable capabilities and workflows that help data scientists develop, deploy, and maintain models efficiently.

Key projects include developing shared libraries for authentication, authorization, logging, and reporting, and automating the creation of model development environments with connectivity to Snowflake schemas. The developer will collaborate with data scientists and engineering teams to build scalable, reliable solutions that support model deployment, monitoring, versioning, and governance.

Key Responsibilities

• Develop and maintain Python-based solutions within Databricks to support AI enablement and model operations.
• Build reusable libraries and components for common capabilities, including authentication, authorization, logging, and reporting.
• Automate the creation and configuration of model development environments, including connectivity to Snowflake schemas.
• Develop automated workflows and CI/CD pipelines to support model testing, deployment, versioning, monitoring, and retraining.
• Implement ingestion and scoring pipelines, and adapt Python, Scala, and SQL code for API and web-based access.
• Develop APIs and integrations connecting data pipelines, databases, and enterprise systems.
• Collaborate with data science, actuarial, engineering, and citizen developer teams to translate business requirements into technical solutions.
• Support data preparation, cleansing, schema design, and analysis for machine learning initiatives.
• Apply ModelOps best practices for reliability, access controls, documentation, governance, and regulatory compliance.
• Troubleshoot workflow and integration issues and optimize the performance of automated solutions.
• Develop familiarity with insurance modeling applications, including mortality, morbidity, and fraud.

Required Qualifications

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, Statistics, or a related field.
• Five or more years of data engineering development experience, including software development and automation.
• Advanced Python programming skills.
• Hands-on experience building solutions within Databricks, including reusable libraries, integrations, or automated workflows.
• Strong experience with database platforms such as Snowflake, Oracle, or Microsoft SQL Server.
• Basic familiarity with Linux/UNIX command-line environments.
• Strong analytical and problem-solving skills.
• Strong written and verbal communication skills, with the ability to explain technical concepts to business and technical audiences.
• Ability to work independently, collaborate across teams, and manage multiple priorities in a deadline-driven environment.

Preferred Qualifications

• Master’s degree in Computer Science, Data Engineering, Information Systems, Statistics, or a related field.
• Experience integrating Databricks solutions with Snowflake.
• Experience developing and maintaining Jenkins CI/CD pipelines.
• Experience with DevOps practices and Infrastructure as Code tools, including Terraform or AWS CloudFormation.
• Knowledge of AWS services such as EMR, Step Functions, Lambda, EC2, S3, RDS, DynamoDB, and Bedrock.
• Experience with ModelOps or MLOps practices, including model deployment, versioning, monitoring, governance, and automated retraining.
• Experience with Scala, Java, or C#.
• Familiarity with Domino Data Lab.
• Knowledge of insurance risk analysis.