Offer summary

Qualifications:

At least 5 years of experience in MLOps or related fields., Proficiency in deploying and managing machine learning models in production., Strong programming skills in Python and experience with ML pipeline tools like Kubeflow or MLflow., Knowledge of cloud platforms such as AWS, GCP, or Azure..

Key responsibilities:

Design and implement scalable MLOps pipelines for data ingestion, training, and deployment.

Collaborate with cross-functional teams to develop and maintain fraud detection systems using machine learning.

Build and maintain internal tools for model versioning, monitoring, and CI/CD processes.

Own the full lifecycle of machine learning models from development to incident response.

Job description

Secure Global Money Transfers with CuttingEdge Technology

Join our mission to protect crossborder transactions, helping customers send money safely worldwide.

As a Senior MLOps Engineer in our AntiFraud & Compliance team, youll architect highperformance systems that detect fraud and enforce regulatory compliance.

Our ML stack focuses on tabular modeling for fraud detection and prevention.

What Youll Do:Develop and implement a comprehensive MLOps strategy that enables the seamless integration of machine learning models into our environment.
Design, implement, and maintain scalable and automated MLOps pipelines (data ingestion, training, evaluation, deployment, and monitoring).
Build internal tools or integrate existing solutions for versioning, model registry, CICD, and observability.
Collaborate with crossfunctional 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

Were Looking For:
5+ years of professional experience in MLOps or a related field.
Experience deploying and managing machine learning models in production environments.
Understanding ML lifecycle, 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 CICD pipelines for ML workflows using GitHub Actions, GitLab CI, Argo, Jenkins, etc.
Experience deploying models in DockerKubernetes 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 SQLNoSQL databases and distributed systems.
Knowledge of fraud prevention, fintech, or compliance.
Strong communication skills (English B2+)
Familiarity with Golang, .NET would be a plus.

Remote work flexibility – work from anywhere.
B2B contract with competitive gross compensation in USD.
Toptier 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 highquality English lessons.
A few words about us:
IDT Corporation is a global communications company founded in 1990 and headquartered in Newark, New Jersey. We are industry leaders in prepaid communication and payment services and one of the largest international voice carriers. We are listed on the NYSE, employ over 1800 people across 20 countries, and have over $1.5 billion in revenues.

We are not ”another big IT corporation”— we encourage and support inhouse entrepreneurs in developing their ideas into business actions.

We understand the challenge of being apart from those who matter most. Boss Revolution is our flagship brand. It includes International Calling, Mobile Top Up, and Money Transfer services. It enables people to keep in touch with family and friends around the world as well as to send money to more than 50 countries with low fees and great exchange rates.