Senior ML Engineer (AWS)

TL;DR

Senior ML Engineer (AWS): Build, train, and deploy machine learning models using AWS SageMaker with an accent on data storage, processing, and analysis with Redshift and S3. Focus on managing workloads on EMR, orchestrating pipelines with Spark and Airflow, and integrating models into production.

Location: Hybrid in Bucharest, Romania

Company

25-year IT consulting firm established in Vienna with 500+ engineers, delivering enterprise systems, automation, and digital platforms across BSFI, telecom, retail, energy, and more.

What you will do

• Build, train, and deploy ML models using AWS SageMaker and managed infrastructure.
• Handle data storage, processing, and analysis with Amazon Redshift and S3.
• Orchestrate large-scale data pipelines using Apache Spark and Airflow.
• Manage and optimize ML workloads on Amazon EMR.
• Collaborate with data engineers for seamless model integration into production.
• Implement model versioning, monitoring, and continuous deployment best practices.

Requirements

• Bachelor's or Master's in Computer Science, Statistics, Mathematics, or related field.
• Proven experience designing, building, and deploying production-grade ML models.
• Extensive AWS experience: SageMaker, Redshift, S3, EMR, and related services.
• Strong Python proficiency with data science libraries (NumPy, Pandas, Scikit-learn).
• Expertise in Airflow and Spark.
• Excellent problem-solving, analytical, communication, and collaboration skills.

Culture & Benefits

• Premium medical package, lunch tickets, Pluxee Card, Bookster subscription.
• 13th salary, yearly bonuses, flexible working with openness to remote.
• Supportive culture emphasizing ownership, autonomy, work-life balance, flat hierarchy.
• Team events, international exposure, project choice aligned with career goals.
• Learning platforms (Pluralsight, Udemy), certifications, mentorship, career growth.