AWS ML Software Engineer

We are seeking a talented and motivated Software Engineer with hands-on experience in Amazon Web Services (AWS) Machine Learning tools and AWS-native time series databases (e.g., Amazon Timestream). The ideal candidate is passionate about designing scalable data solutions, deploying ML models in the cloud, and working at the intersection of software engineering and data science.

Key Responsibilities:

• Design, develop, and deploy scalable software applications leveraging  on a real world ML services (e.g., SageMaker, Rekognition, Forecast, etc.).
• Build and maintain robust data pipelines and infrastructure for handling time series data using AWS tools such as Amazon Timestream or Amazon Managed Prometheus.
• Collaborate with data scientists, analysts, and other engineers to integrate ML models into production environments
• Write clean, maintainable, and well-tested code following best practices in cloud-native software engineering.
• Monitor and optimize performance of ML models and time series databases for reliability and cost-efficiency.
• Automate deployment and infrastructure using tools like AWS CloudFormation, CDK, or Terraform.
• Ensure data security, privacy, and compliance in all cloud-based solutions.

Requirements

Required:

•  3+ years of software engineering experience.
• Strong experience with AWS ML services (e.g., SageMaker, Forecast, Comprehend, etc.).
• Extensive hands-on experience with AWS time series solutions (e.g., Amazon Timestream, IoT Analytics, Prometheus).
• Proficiency in at least one programming language such as Python, Java, or Go.
• Experience with serverless technologies and event-driven architecture (e.g., Lambda, EventBridge).
• Familiarity with containerization (Docker) and orchestration (ECS, EKS).
• Strong understanding of CI/CD, testing frameworks, and version control (Git).

Preferred:

• Experience with streaming data and real-time analytics (e.g., Kinesis, Kafka).
• Knowledge of time series forecasting or anomaly detection techniques.
• AWS Certification (e.g., AWS Certified Machine Learning – Specialty, Solutions Architect).

Benefits

Compensation & Perks

• Salary: We will settle on the  exact compensation amount based on prior experience and skills.
• Private health insurance & Life Insurance  from day #1
• Health management scheme (weekly sessions &monthly challenges)
• 25 vacation days
• Team events tech oriented and more
• International network
• Lunch in the office & Go For Eat vouchers
• Employee referral programme/ bonus

Dedicated budget for:

• Employee education ~ 800€
• Hardware selection (MacBook or Lenovo ThinkPad) with your own mobile ~ 3000€