About the role
About Qualysoft
· 25 years of experience in software engineering, established in Vienna, Austria
· Active in Romania since 2007, with office in central Bucharest (Bd. Iancu de Hunedoara 54B)
· Delivering End to End IT Consulting Services - From Team Augmentation and Dedicated Teams to Custom Software Development
· We deliver scalable enterprise systems, intelligent automation frameworks, and digital transformation platforms
· Cross-industry experience by sustaining global players in BSFI (Banking, financial services and insurance), Telecom,Retail & E-commerce, Energy and Utilities, Automotive, Manufacturing, Logitics, High Tech
· Global Presence: Switzerland, Germany, Austria, Sweden, Hungary, Slovakia, Serbia, Romania, and Indonesia
· International team of 500+ software engineers
· Strategic partnerships: Microsoft Cloud Certified Partner, Tricentis Solutions Partner in Test Automation and Test Management, Creatio Exclusive Partner, Doxee Implementation Partner
· Powered by cutting-edge technologies: AI, Data & Analytics, Cloud, DevOps, IoT, and Test Automation.
· Project beneficiaries ranging from large-scale enterprises to startups
· Stable growth and revenue increase year over year, a resilient organisation in volatile IT market conditions
· Quality-first mindset, culture of innovation, and long-term client partnerships
· Global and local reach – trusted by key industry players in Europe and the US
Responsibilities
• Build, train, and deploy machine learning models efficiently with the managed infrastructure and automation capabilities of AWS SageMaker;
• Utilize Amazon Redshift and S3 for data storage, processing, and analysis;
• Utilize Apache Spark and Airflow for large-scale data processing and pipeline orchestration;
• Manage and optimize machine learning workloads on Amazon EMR;
• Proficiency in Python and its data science libraries (e.g., NumPy, Pandas, Scikit-learn) for data manipulation, modeling, and analysis;
• Collaborate with data engineers to ensure seamless integration of ML models into production environments;
• Implement best practices for model versioning, monitoring, and continuous deployment.
Qualifications
• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field;
• Proven experience designing, building, and deploying production-grade machine learning models;
• Extensive experience with AWS services like SageMaker, Redshift, S3, EMR, and other relevant AWS data and ML services;
• Strong proficiency in Python and its data science (e.g., NumPy, Pandas, Scikit-learn etc.);
• Expertise in Airflow and Spark;
• Excellent problem-solving and analytical skills;
• Strong communication and collaboration skills.
Tech stack
Python
Arrangement Hybrid
Location RO
Posted 85d ago
.*
findatechjobTech jobs straight from company career pages. No recruiters, no middlemen, no spam.
Countries
Languages
Company
© 2026 findatechjob · Logos provided by Logo.dev