Machine Learning Engineer / Data Scientist (Mid-Level)

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.