Machine Learning Administrator (Remote Work)
Salário Estimado
R$ 9.867,00 - R$ 14.801,00
Regular
Score da Vaga
Descrição da Vaga
This position is posted by Jobgether on behalf of a partner company.
We are currently looking for a Machine Learning Administrator - REMOTE.
This role plays a critical part in managing and optimizing machine learning models within the Databricks platform.
The ideal candidate will actively contribute to the administration of enterprise data architectures, particularly focused on Department of Defense data-driven projects.
You will have the opportunity to work remotely, ensuring that complex AI/ML pipelines operate smoothly and securely.
Your expertise will directly impact the effectiveness and efficiency of machine learning initiatives in collaboration with various teams.
The position allows for a blend of remote work and potential travel, making it versatile and accommodating.
Accountabilities • Manage machine learning model versioning, lineage tracking, and compliance with governance policies.
Requirements • Master's degree in Computer Science, Information Science, Artificial Intelligence, Geospatial Science, GIS, Data Science, Business Analytics, Cognitive Science, or a related field, or eleven (11) years of equivalent experience.
Benefits • Flexible working environment with the option to work from home.
Why Apply Through Jobgether? We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements.
Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company.
The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best! Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer.
This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR).
You may exercise your rights (access, rectification, erasure, objection) at any time.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses.
These tools assist our recruitment team but do not replace human judgment.
Final hiring decisions are ultimately made by humans.
If you would like more information about how your data is processed, please contact us.
Requisitos
- Master's degree in Computer Science, Information Science, Artificial Intelligence, Geospatial Science, GIS, Data Science, Business Analytics, Cognitive Science, or a related field, or eleven (11) years of equivalent experience
- Demonstrated expertise in ontology design and semantic data modeling
- Proficiency in W3C standards (RDF, OWL, SHACL) and supporting frameworks
- Proficiency in Java and Python for ontology-driven application development
- Experience with the Stardog Knowledge Graph platform
- Experience with Bash scripting for automation tasks
- Hands-on experience with Esri data tools including ArcGIS
- Background in DevSecOps practices, version control systems (e.g., Git) and CI/CD pipelines
- Strong analytical skills and attention to detail
- Ability to manage and prioritize complex project tasks
Responsabilidades
- This role plays a critical part in managing and optimizing machine learning models within the Databricks platform
- The ideal candidate will actively contribute to the administration of enterprise data architectures, particularly focused on Department of Defense data-driven projects
- You will have the opportunity to work remotely, ensuring that complex AI/ML pipelines operate smoothly and securely
- Your expertise will directly impact the effectiveness and efficiency of machine learning initiatives in collaboration with various teams
- The position allows for a blend of remote work and potential travel, making it versatile and accommodating
- Manage machine learning model versioning, lineage tracking, and compliance with governance policies
- Implement and monitor ML infrastructure, optimizing compute resource allocation across cloud and on-premises environments
- Support validation of AI/ML pipelines, ensuring models remain accurate, explainable, and aligned with operational objectives
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