Machine Learning Engineer
منذ 2 أيام
Dubai, Dubai Emirate, الإمارات العربية المتحدة
DATAMAZE . AI
دوام كامل
220,345 € - 312,155 € عقد
مجانًا عبر البريد الإلكتروني أو Google
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مجانًا عبر البريد الإلكتروني أو Google
About The Role
We are looking for a highly motivated Machine Learning Engineer / Data Scientist to join our dynamic team. In this mid-level role, you will leverage your expertise in data science and machine learning to design, build, and deploy innovative models and solutions that address real-world challenges.
Location:
Hyderabad, India / Dubai, UAE
Job Type
Full-time
Key Responsibilities
- Model Development: Design, train, and evaluate machine learning models to solve business problems such as classification, regression, clustering, and recommendation.
- Data Preparation: Work with large and complex datasets, performing data cleaning, preprocessing, and feature engineering to optimize model performance.
- Model Deployment: Deploy machine learning models into production environments, ensuring scalability and robustness.
- Algorithm Selection: Research and implement state-of-the-art algorithms and methodologies to enhance model accuracy and efficiency.
- Collaboration: Collaborate with data engineering teams to build data pipelines and ensure efficient data flow for machine learning workflows.
- Visualization and Reporting: Create clear and actionable visualizations and reports to communicate findings and results to stakeholders.
- Monitoring and Maintenance: Monitor model performance in production, address drift or bias issues, and optimize models as needed.
- Tool Development: Build tools and frameworks to enable rapid experimentation and iteration of machine learning models.
- Documentation: Maintain comprehensive documentation for models, experiments, and processes. Qualifications
Education:
Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics, or a related field (or equivalent experience). Technical
Skills:
- Strong programming skills in Python, R, or similar languages.
- Experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, Scikit-learn, or Keras.
- Proficiency in data manipulation and analysis using tools like Pandas, NumPy, and SQL.
- Experience with big data technologies such as Spark, Hadoop, or similar.
- Knowledge of cloud platforms and services (e.g., AWS SageMaker, Google AI Platform, Azure ML).
- Familiarity with MLOps practices and tools for CI/CD in machine learning workflows.
- Understanding of data visualization tools like Matplotlib, Seaborn, or Tableau.
- Strong grasp of statistical methods, probability, and optimization techniques.
Experience:
- 3–5 years of experience in machine learning, data science, or a related field.
- Proven experience building and deploying machine learning models in production.
- Experience with natural language processing (NLP), computer vision, or time-series analysis is a plus. Soft
Skills:
- Strong problem-solving and analytical thinking abilities.
- Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
- Ability to work independently and collaboratively within a team.
- Curiosity and eagerness to stay updated on the latest advancements in machine learning and AI.