Information Technology
Full-Time
Delphie Consulting services
Overview
Job Summary
We are seeking an experienced and skilled Senior Machine Learning Engineer with a strong background in Python and hands-on expertise in building and deploying machine learning models.
The ideal candidate will possess deep knowledge of machine learning algorithms, Unix-based operating systems, and modern software development practices.
This is a critical role that combines data science, engineering, and agile product development to solve real-world problems.
Key Responsibilities
We are seeking an experienced and skilled Senior Machine Learning Engineer with a strong background in Python and hands-on expertise in building and deploying machine learning models.
The ideal candidate will possess deep knowledge of machine learning algorithms, Unix-based operating systems, and modern software development practices.
This is a critical role that combines data science, engineering, and agile product development to solve real-world problems.
Key Responsibilities
- Design, develop, and deploy machine learning models using Python and libraries such as Scikit-learn, TensorFlow, or PyTorch.
- Apply machine learning techniques including supervised and unsupervised learning methods (e.g, classification, clustering).
- Implement and optimize clustering algorithms like K-Means, Fuzzy Clustering, or DBSCAN.
- Work on data preprocessing, feature engineering, model evaluation, and model tuning.
- Collaborate with cross-functional teams in an Agile environment.
- Manage version control and codebase using Git.
- Operate within Unix-based environments (preferably RHEL).
- Interact with relational databases such as Oracle for data access and manipulation.
- Document and track development tasks using project management tools.
- Programming Languages : Python
- Machine Learning : Strong understanding of ML algorithms, model training, and libraries (Scikit-learn, TensorFlow, PyTorch)
- ML Concepts : Supervised/Unsupervised learning, Classification, Clustering (e.g, K-Means, DBSCAN, Fuzzy)
- Operating Systems : RHEL or any Unix-based OS
- Databases : Oracle or similar RDBMS
- Version Control : Git
- Development Methodologies : Agile/Scrum
- Experience with issue tracking and lifecycle tools like Azure DevOps or JIRA
- Exposure to Big Data models, libraries, and processing frameworks
- Familiarity with data science workflows and techniques
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