Sr AI/Machine Learning Analyst

About Sinch:

Sinch is a global leader in the growing market for Communication Platforms as a Service and mobile customer engagement. We are specialists in allowing businesses to reach everyone on the planet, in seconds or less, through mobile messaging, email, voice, and video.

With presence in more than 50 countries, whether you know us or not, you’ve definitely used our tech. We reach every phone on earth, with over 147 billion conversations every year.

Sinch's core values are Make it Happen, Dream Big, Keep it Simple and Win Together. These values describe how our global organization works and inspire every of our more than 3,000 employees across 55 different countries.

About the Role:

We are looking for a Senior Machine Learning Engineer to join our Anti-Fraud team. This role sits at the intersection of experimentation, scalable systems, and real-world fraud prevention.

As AI-driven abuse patterns evolve, fraud detection becomes increasingly complex. You will work in a ML environment where model development, production systems, and platform scalability are equally critical.

This is not a research-only role nor a pipeline-only role. We are looking for an engineer who is equally comfortable developing models and operating them in production at scale.

You will partner closely with other senior engineers to co-own the evolution of our ML pipelines, and model lifecycle.

Responsibilities:

• Design, train, develop, and deploy production-grade machine learning models (e.g., text classification, anomaly detection, image classification)

• Own the end-to-end ML lifecycle: experimentation, validation, deployment, monitoring, and continuous improvement

• Build and maintain scalable data pipelines to preprocess, validate, and transform large datasets

• Ensure ML systems are reliable, observable, and scalable in high-volume environments

• Collaborate with Engineering, Product, and Anti-Fraud stakeholders from problem definition to solution delivery

• Implement and optimize machine learning algorithms using Python, Tensorflow, PyTorch, or other relevant technologies

• Design and develop data pipelines to preprocess, transform, and clean large datasets for machine learning models

• Optimize model performance and system efficiency in cloud environments (e.g., AWS)

• Promote best practices in experimentation, reproducibility, monitoring, and documentation

• Stay up-to-date with the latest trends and advances in Machine Learning

• Collaborate with engineers across different seniority levels and technical domains, contributing to shared ownership, knowledge exchange, and overall team growth

Qualifications:

• 5+ years of experience building and deploying Machine Learning systems in production environments

• Strong Python skills and hands-on experience with ML libraries (Scikit-learn, TensorFlow, PyTorch, etc.)

• Experience working with large-scale data processing frameworks (e.g., Databricks, Spark)

• Experience designing and maintaining ML pipelines in production

• Solid understanding of system design, scalability, and reliability principles

• Experience with cloud platforms (preferably AWS)

• Strong problem-solving skills and ability to operate with autonomy

• Advanced or fluent English

Nice-to-have:

• Experience with large-scale text classification, anomaly detection, or image classification systems

• Experience in fraud detection or high-risk/high-volume environments

• Familiarity with orchestration tools (Airflow, Dagster, etc.)

• Experience with Docker and Kubernetes

• Experience working within Lakehouse architectures