Senior MLOps Engineer - Anti-Fraud & Compliance Platform
WFA Digital Insight
As the demand for skilled MLOps engineers continues to rise, with a 25% growth in job openings in 2025, professionals with expertise in deploying and managing machine learning models are in high demand. IDT Corporation's commitment to innovation and its global presence make this role particularly appealing. With the increasing importance of protecting cross-border transactions, candidates with experience in fraud prevention and compliance will have a competitive edge. Before applying, candidates should be prepared to showcase their technical skills and understanding of the ML lifecycle, as well as their ability to collaborate with cross-functional teams.
Job Description
About the Role
The Senior MLOps Engineer role at IDT Corporation is a crucial part of the Anti-Fraud & Compliance team, focusing on developing and implementing comprehensive MLOps strategies to integrate machine learning models seamlessly into the environment. This role requires a deep understanding of the ML lifecycle, including model training, evaluation, deployment, and monitoring. As a senior member of the team, the successful candidate will be responsible for designing, implementing, and maintaining scalable and automated MLOps pipelines.The role involves collaborating with cross-functional teams, including data scientists, software engineers, and other stakeholders, to understand model requirements, deployment needs, and data dependencies. The Senior MLOps Engineer will also be responsible for building internal tools or integrating existing solutions for versioning, model registry, CI/CD, and observability.
IDT Corporation is a global communications company with a strong commitment to innovation and customer protection. The company's focus on secure global money transfers and its dedication to using cutting-edge technology make this role an exciting opportunity for professionals looking to make a significant impact.
What You Will Do
- Develop and implement a comprehensive MLOps strategy for the integration of machine learning models into the environment.
- Design, implement, and maintain scalable and automated MLOps pipelines, including data ingestion, training, evaluation, deployment, and monitoring.
- Build internal tools or integrate existing solutions for versioning, model registry, CI/CD, and observability.
- Collaborate with cross-functional teams to design, deploy, and manage scalable infrastructure for machine learning workloads.
- Own the full development lifecycle from design to incident response.
- Work closely with data scientists, software engineers, and other stakeholders to understand model requirements, deployment needs, and data dependencies.
- Enhance fraud detection systems using machine learning.
- Develop and maintain technical documentation for MLOps pipelines and processes.
- Participate in code reviews and contribute to the improvement of the codebase.
- Stay up-to-date with the latest developments in MLOps and machine learning.
What We Are Looking For
- 5+ years of professional experience in MLOps or a related field.
- Experience deploying and managing machine learning models in production environments.
- Understanding of the ML lifecycle, including model training and evaluation workflows, reproducibility, and model governance.
- Experience building internal MLOps platforms or developer tools.
- Experience with ML pipeline orchestration tools (e.g., Kubeflow, MLflow, Airflow, Metaflow, SageMaker Pipelines).
- Knowledge of setting up CI/CD pipelines for ML workflows using GitHub Actions, GitLab CI, Argo, Jenkins, etc.
- Experience deploying models in Docker/Kubernetes environments.
- Strong knowledge of cloud platforms: AWS, GCP, or Azure.
- Experience with setting up tools like Prometheus, Grafana for model & pipeline observability.
- Strong programming skills in Python.
- Experience with SQL/NoSQL databases and distributed systems.
- Strong communication skills (English B2+).
Nice to Have
- Familiarity with Golang, .NET.
- Knowledge of fraud prevention, fintech, or compliance.
- Experience with containerization using Docker.
- Understanding of agile development methodologies.
Benefits and Perks
- Remote work flexibility – work from anywhere.
- B2B contract with competitive gross compensation in USD.
- Top-tier hardware to support your productivity.
- A challenging role in a team of skilled professionals.
- Continuous learning and career growth opportunities.
- Coverage for professional development: training, seminars, and conferences.
- Access to high-quality English lessons.
- Opportunity to work with a global company and contribute to the development of secure money transfer services.
How to Stand Out
- Tip: Showcase your experience with MLOps tools and technologies, such as Kubeflow, MLflow, or Airflow, and be prepared to explain how you have used them in previous roles.
- Tip: Highlight your understanding of the ML lifecycle, including model training, evaluation, deployment, and monitoring, and provide examples of how you have managed these processes in the past.
- Tip: Be prepared to discuss your experience with cloud platforms, such as AWS, GCP, or Azure, and how you have used them to deploy machine learning models.
- Tip: Emphasize your strong programming skills in Python and your experience with SQL/NoSQL databases and distributed systems.
- Tip: Research IDT Corporation and its commitment to innovation and customer protection, and be prepared to explain how your skills and experience align with the company's goals.
- Tip: Be prepared to discuss your experience with collaboration tools, such as GitHub or GitLab, and how you have used them to work with cross-functional teams.
- Tip: Consider creating a portfolio that showcases your experience with machine learning and MLOps, and be prepared to discuss your projects and achievements during the interview process.
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