
Machine Learning
Há 2 dias
Overview
Join to apply for the Machine Learning (ML) Ops Engineer role at Bizmoni - The Next Gen AI Super APP .
Bizmoni is the worlds first AI Super App designed to help anyone earn, learn, and grow in the AI era. We are building a global, fully remote team to shape the future of financial technology. Our mission is to make powerful AI-driven financial and business tools accessible to everyone from individuals starting side hustles to enterprises scaling globally.
Location and EmploymentLocation: Fully remote
Employment type: Part-time
What You'll Do- Design, build, and maintain end-to-end machine learning infrastructure ensuring scalability, high availability, and performance.
- Automate ML pipelines with Docker, Kubernetes, and CI/CD frameworks.
- Collaborate with data scientists and engineers to streamline model deployment.
- Monitor and optimize models in production with observability tools (e.g., Prometheus, Grafana, ELK).
- Manage and optimize cloud infrastructure (AWS, Azure, or GCP) for efficiency and cost.
- Ensure compliance and security protocols for sensitive financial data.
- Provide support and maintenance to ensure the reliability of ML applications.
- Proven experience as an MLOps Engineer or similar role (fintech or AI startup experience is a plus).
- Strong programming skills in Python (preferred); familiarity with Java or Scala is a plus.
- Experience with ML frameworks and pipeline orchestration (MLflow, Airflow, Kubeflow, or SageMaker).
- Hands-on experience with cloud services (AWS, Azure, or GCP).
- Solid knowledge of containerization and orchestration (Docker, Kubernetes).
- Familiarity with Git and CI/CD tools.
- Strong understanding of ML algorithms and their real-world applications.
- Excellent communication and collaboration skills in a remote, cross-timezone team environment.
- Bachelors or Masters degree in Computer Science, Data Science, or related field (or equivalent experience).
- Be part of a mission-driven company building the future of AI-powered FinTech.
- Fully remote role with a global, diverse team.
- Equity-based compensation with the potential for future full-time opportunities.
- Culture of innovation, collaboration, and ownership.
- Are you open to equity-based compensation?
- Are you able to dedicate 16 hours weekly to our project?
If your answers are YES , then we are happy to meet you
Recruitment Process- Interview with Data Science Department Manager & TA Partner.
- Offer (based on final positive feedback).
Please submit your English CV. Only shortlisted candidates will be invited to interview. Thank you.
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