Machine Learning Engineer / Data Scientist (Mid-Level)

About the role

Datamaze, an AI, data and analytics consulting firm, is looking for a highly motivated Machine Learning Engineer / Data Scientist for a mid-level position. You will design, build and deploy models and solutions that turn complex datasets into actionable insights, working with data engineers, product managers and software developers. The role is based in Hyderabad, India or Dubai, UAE, full-time.

Key responsibilities

• Design, train and evaluate machine learning models for tasks such as classification, regression, clustering and recommendation.
• Clean, preprocess and engineer features in large and complex datasets.
• Deploy models into production and monitor their performance, addressing drift or bias.
• Research and implement state-of-the-art algorithms to improve accuracy and efficiency.
• Build data pipelines with data engineering teams and create visualizations and reports for stakeholders.
• Build tools and frameworks for rapid experimentation and keep documentation of models, experiments and processes.

Required profile

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, Statistics or a related field, or equivalent 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.
• Natural language processing, computer vision or time-series analysis experience is a plus.
• Strong problem-solving, analytical and communication skills, able to explain technical concepts to non-technical people.

Required skills

• Programming in Python, R or similar.
• Machine learning libraries such as TensorFlow, PyTorch, Scikit-learn or Keras.
• Data manipulation with Pandas, NumPy and SQL; big data tools such as Spark or Hadoop.
• Cloud platforms such as AWS SageMaker, Google AI Platform or Azure ML.
• MLOps practices and CI/CD for machine learning; data visualization tools such as Matplotlib, Seaborn or Tableau.