Senior ML Engineer
BucharestOn-siteFull-time
AI Summary
Senior ML Engineer designs, builds, and deploys production-grade ML models, leveraging AWS SageMaker, Spark, Airflow, and Python for end-to-end data pipelines and integration into production.
About this 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.
Skills
AirflowApache SparkAWS EMRAWS RedshiftAWS S3AWS SageMakerCI/CD For MLData EngineeringData Pipeline OrchestrationData ProcessingMachine LearningModel MonitoringModel VersioningNumPyPandasProduction ML DeploymentPythonSciKit-LearnSQL
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