- Company Name
- TEADS
- Job Title
- Senior Machine Learning Engineer – Backend, Data Engineering & Infrastructure
- Job Description
-
**Job Title:** Senior Machine Learning Engineer – Backend, Data Engineering & Infrastructure
**Role Summary**
Senior ML Engineer to design, optimize, and manage backend systems, ML workflows, and data engineering infrastructure for scalable machine learning solutions. Focus on high-performance, low-latency systems and seamless integration of models into production.
**Expectations**
Proven expertise in backend development, ML pipeline engineering, cloud infrastructure, and DevOps practices. Experience building end-to-end solutions for ML model integration, data pipeline optimization, and distributed system performance.
**Key Responsibilities**
- architect and optimize backend systems for ML workflows, ensuring scalability and efficiency.
- develop and maintain ML pipelines for preprocessing, training, evaluation, and deployment.
- engineer large-scale data pipelines using Spark, Airflow, BigQuery, AWS S3.
- manage AWS Batch for distributed training, balancing compute efficiency and cost.
- resolve infrastructure challenges in cloud environments (AWS, GCP), prioritizing security, scalability.
- collaborate with data scientists and engineers to deliver production-ready ML solutions.
- automate infrastructure deployment and testing with CI/CD, Terraform, Docker, Kubernetes.
- implement testing frameworks and monitoring for system performance and reliability.
**Required Skills**
- Backend programming: Python, Java, Scala.
- ML pipeline development: model training, data preprocessing, deployment.
- Data engineering tools: Apache Spark, Airflow, BigQuery, AWS S3.
- Cloud infrastructure: AWS (Batch, EC2, S3), GCP (preferred).
- DevOps: CI/CD pipelines, Terraform, Docker, Kubernetes.
- Optimization: performance engineering, low-latency system design.
- Problem-solving: complex backend and infrastructure challenges.
- Communication: clear articulation of technical solutions to cross-functional teams.
**Required Education & Certifications**
Bachelor’s/Master’s in Computer Science, Software Engineering, or related field. No specific certifications required.