- Company Name
- dataroots
- Job Title
- Expert Machine Learning Engineer
- Job Description
-
Job title: Expert Machine Learning Engineer
Role Summary: Design, develop, deploy and optimize production‑ready machine learning and deep learning models for diverse industry clients. Lead end‑to‑end ML projects, mentor teammates, and ensure continuous improvement of data‑driven solutions.
Expectations: Produce scalable, high‑performance models within client timelines; maintain rigorous code quality and documentation; communicate complex concepts clearly to technical and non‑technical stakeholders; stay current with ML research and industry best‑practice.
Key Responsibilities:
- Build and tune supervised, unsupervised and generative models using Python, SQL and relevant libraries (scikit‑learn, TensorFlow, PyTorch).
- Deploy models to cloud platforms or on‑premises containers, implementing MLOps pipelines with Docker, Kubernetes, Airflow/Prefect/Dagster.
- Design data pipelines and feature engineering workflows, collaborating with Data Engineers and Cloud Architects.
- Monitor model performance post‑deployment, implement drift detection and retraining strategies.
- Mentor junior engineers, conduct code reviews, and share knowledge through workshops or technical notes.
- Translate business requirements into ML solutions, preparing deliverables and presentations for clients.
- Evaluate and integrate Generative AI (GenAI) capabilities where appropriate.
Required Skills:
- Advanced knowledge of machine learning theory, statistical modeling, and deep learning architectures.
- Proficiency in Python and SQL; experience with additional languages (Java, Scala, R) is a plus.
- Hands‑on experience with MLOps practices, including model versioning, CI/CD, and monitoring.
- Expertise in containerization (Docker, Kubernetes) and workflow orchestration (Airflow, Prefect, Dagster).
- Solid understanding of cloud services (AWS, Azure, GCP) and data‑engineering fundamentals.
- Strong analytical mindset, problem‑solving skills, and ability to manage large datasets.
- Excellent written and oral communication; capability to translate technical insights into actionable client recommendations.
- Fluency in English; proficiency in Dutch or French is highly desirable.
Required Education & Certifications:
- Master’s degree or Ph.D. in Computer Science, Statistics, Data Science, Engineering or related quantitative field.
- At least 4 years of industry experience in machine learning, data science or related roles.
- Relevant certifications (e.g., AWS Certified Machine Learning, Azure AI Engineer Associate, GCP Professional Data Engineer) are advantageous but not mandatory.