Looking for Data/Machine Learning Engineer to build robust cloud-native and hybrid data/machine learning pipelines. Youll work closely with cross-functional teams including Data Scientists and Solution Architects to support model research and early-stage development.
Responsibilities:
- Build cloud-native and hybrid data/machine learning pipelines.
- Collaborate with Solution Architects Cloud/Backend Engineers Data Security Engineers Data Scientists and Algorithm Developers.
- Develop enterprise-grade tools to support long-term ML research.
- Provide technical support for early-stage research and development.
- Organize clean and manage raw datasets.
- Prepare data for predictive and prescriptive modeling.
- Identify and implement opportunities to automate data processes (e.g. curation validation).
Qualifications :
- Degree in Computer Science or a related field; Masters degree is a plus.
- 10 years of practical experience working with Python and Machine Learning/ data engineering technologies.
- Strong grasp of the Python ecosystem (e.g. NumPy Pandas Scikit-learn).
- Familiarity with coding best practices (e.g. TDD ATDD).
- Understanding of application architecture and design patterns.
- Testing strategies and version control.
- Extensive experience with storage technologies (relational databases NoSQL object storage).
- Solid understanding of Machine Learning workflows and the infrastructure needed to support them.
- Experience with HPC and AWS-based data engineering and analytics platforms.
- Hands-on with ETL and data integration tools (e.g. Talend Kubeflow Spark Tableau Flume Kafka Databricks).
- Comfortable working in a Linux environment.
Additional Information :
- Experience working in global or international teams is a plus.
- Data engineering certifications (e.g. AWS Solution Architect IBM Certified Data Engineer) are a plus
Remote Work :
Yes
Employment Type :
Full-time