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Qualco

MLOps Engineer

Qualco, Frankfort, Kentucky, United States

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Overview

At Quento, the ICT arm of the Qualco Group, we deliver comprehensive and innovative solutions across AI, Digital Engineering, Cloud, and Cybersecurity, helping businesses accelerate digital transformation. With a presence in Greece, Luxembourg, and Belgium, and backed by the expertise of the Qualco Group, we combine deep technical knowledge with strategic partnerships to support business growth. Role

Quento Technologies seeks a highly skilled

MLOps Engineer

to join our team in large and medium scale AI projects for our customers. The ideal candidate will be responsible for designing, building, and maintaining the infrastructure, pipelines, and tooling necessary to deploy, monitor, and scale machine learning ML models in production, ensuring that ML solutions are robust and efficient. Responsibilities

Model Deployment & Automation

Build and manage CI/CD pipelines for machine learning models. Automate model training, testing, and deployment workflows.

Infrastructure & Scalability

Design and maintain scalable infrastructure for ML workloads (cloud, on-prem, or hybrid). Optimize resource utilization across GPUs/CPUs for inference and training.

Monitoring & Reliability

Implement monitoring solutions for model performance, data drift, and system health. Establish alerting and rollback mechanisms for production ML systems.

Collaboration

Work closely with ML engineers to operationalize ML models. Partner with DevOps and software engineering teams to align ML infrastructure with enterprise standards.

Governance & Compliance

Ensure reproducibility, versioning, and traceability of models and datasets. Support compliance with data protection and security regulations.

Qualifications

Education : Bachelor’s or Master’s in Computer Science, Data Science, AI/ML, or related field (or equivalent experience). Technical Skills

Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn). Experience with containerization and orchestration (Docker, Kubernetes). Hands-on with cloud platforms (AWS, Azure, GCP) and their ML services. Familiarity with CI/CD tools (GitHub Actions, Jenkins, GitLab CI). Knowledge of data versioning & workflow orchestration tools (MLflow, DVC, Airflow, Kubeflow).

Experience

2–5 years in MLOps, DevOps, or ML engineering roles. Deploying ML models at scale in production environments. Candidates with strong DevOps background and mentality, that have started exploring the MLOps world will also be seriously considered.

Soft Skills

Strong problem-solving and debugging skills. Ability to communicate complex technical concepts to both technical and non-technical stakeholders. Ability to perform market researches on MLOps platforms, consult on selection of appropriate tools and defend the selection through presentations in technical or non-technical audiences Collaborative mindset with a focus on cross-team alignment. Continuous learner, staying up to date with the latest in ML, DevOps, and cloud technologies.

Life at Qualco

On top of challenging work environment, we are offering: Competitive compensation, ticket restaurant card, and annual bonus programs Cutting-edge IT equipment, mobile and data plan Modern facilities, free coffee and beverages, indoor parking, and company bus Private health insurance, onsite occupational doctor, and workplace counselor Flexible working model, hybrid benefits & home equipment benefits Onsite gym, wellness facilities, and ping pong room Career and talent development tools Mentoring, coaching, personalized annual learning and development plan Employee referral bonus, regular wellbeing, ESG and volunteering activities Your race, gender identity and expression, age ethnicity or disability make no difference in Quento. We want to attract, develop, promote, and retain the best people based only on their ability and behavior. Disclaimer: Quento collects and processes personal data in accordance with the EU General Data Protection Regulation (GDPR). We are bound to use the information provided within your job application for recruitment purposes only and not to share these with any third parties. For more details on the processing of your personal data during the Recruitment procedure, please be informed in the Recruitment Notice, before the submission of your application. #LI-Hybrid

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