Senior Machine Learning Engineer - Backend, Data Engineering & Infrastructure
What will you do? As a Senior Machine Learning Engineer, your mission will be:
- Design, develop, and optimize backend systems for scalable and efficient data processing, particularly in machine learning workflows.
- Develop and maintain ML flows to streamline data preprocessing, model training, evaluation, and deployment, ensuring smooth integration between systems.
- Build and optimize data pipelines using Spark , Airflow , BigQuery , and AWS S3 for handling large-scale data ingestion, transformation, and processing.
- Manage AWS Batch for large-scale distributed training jobs, optimizing compute resources and cost management for ML workflows.
- Solve complex infrastructure challenges , focusing on performance and low-latency systems that support ML and data-heavy applications.
- Collaborate with data scientists , DevOps engineers , and other backend engineers to design end-to-end solutions, integrating ML models with the infrastructure.
- Manage cloud-based infrastructure (AWS, GCP), focusing on cost optimization , security , and scalability for data and ML systems.
- Ensure that all backend systems are tested, optimized, and continuously monitored, including writing, running, and automating unit , functional , and load tests .
- Stay up-to-date with emerging technologies and contribute to the ongoing improvement of backend systems, ML workflows, and data engineering tools.
- Experience with performance engineering , profiling, and optimizing systems for high efficiency and low latency.
- Backend development expertise in Python , Java , and Scala , with a strong understanding of software engineering practices, debugging, and performance optimization.
- Experience building and optimizing ML flows , integrating model training, data preprocessing, and deployment pipelines.
- Hands-on experience with data engineering tools like Spark , Airflow , BigQuery , and AWS S3 , as well as building large-scale data pipelines.
- Proficiency with AWS Batch for managing large-scale compute resources and distributed ML training.
- Familiarity with cloud infrastructures (AWS, GCP), and expertise in managing scalable backend services and data pipelines in production.
- DevOps skills , including experience with CI/CD pipelines , Terraform , Docker , and Kubernetes to automate and manage infrastructure.
- Strong problem-solving abilities to address complex backend and infrastructure issues related to performance, scalability, and efficiency.
- Excellent communication skills for working cross-functionally, explaining complex concepts clearly to technical and non-technical teams.
- Understanding data science principles and machine learning concepts.
- Familiarity with ML frameworks such as TensorFlow or PyTorch .
- The AI department currently consists of 50 people who are a mix of data scientists, machine learning and backend engineers
- The department provides technologies that power outcomes of campaigns with a total yearly turn over of $1.7B
- Runs large scale prediction and control systems for ad delivery, dealing with millions of live ads, doing more than a billion predictions per second based on large on-line trained models being updated every 5 minutes
- Impact: Your work will directly empower hundreds of engineers and significantly impact Teads' ability to innovate and deliver.
- Challenge: You'll tackle complex, high-scale infrastructure problems at the forefront of cloud-native and AI technologies.
- Growth: We foster a culture of continuous learning, professional development, and technical excellence.
- Collaboration: Work alongside talented and passionate engineers in a supportive and collaborative environment.
- We've merged two open internet category leaders-Outbrain and Teads-to create the 'new' Teads, a unified omnichannel platform that drives results from branding to performance across all screens, including CTV, mobile, and web.
- As part of our team, you'll thrive in a collaborative and forward-thinking environment that fosters innovation, creative problem-solving, and continuous learning.
- Teads is committed to your success, offering the support, tools, and development opportunities you need to excel in your role.
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