Machine Learning Engineer / Data Scientist (Mid-Level)
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Key skills for this role
About the Role
Datamaze is hiring a mid-level Machine Learning Engineer / Data Scientist to design, build, and deploy ML models. The role involves working with large datasets, deploying models to production, and collaborating with cross-functional teams to drive business value.
Key Skills for This Role
Responsibilities
- Design, train, and evaluate machine learning models for classification, regression, clustering, and recommendation
- Perform data cleaning, preprocessing, and feature engineering on large datasets
- Deploy machine learning models into production environments ensuring scalability and robustness
- Research and implement state of the art algorithms to enhance model accuracy and efficiency
- Collaborate with data engineering teams to build data pipelines
- Create visualizations and reports to communicate findings to stakeholders
- Monitor model performance in production, address drift or bias, and optimize models
- Build tools and frameworks for rapid experimentation and iteration of ML models
- Maintain comprehensive documentation for models, experiments, and processes
Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, Statistics, or related field (or equivalent experience)
- 3–5 years of experience in machine learning, data science, or related field
- Strong programming skills in Python, R, or similar languages
- Experience with machine learning libraries such as TensorFlow, PyTorch, Scikit learn, or Keras
- Proficiency in data manipulation using Pandas, NumPy, and SQL
- Experience with big data technologies such as Spark, Hadoop, or similar
- Knowledge of cloud platforms (e.g., AWS SageMaker, Google AI Platform, Azure ML)
- Familiarity with MLOps practices and CI/CD for ML workflows
- Proven experience building and deploying ML models in production
Full Job Posting
About The Role
- Looking for a highly motivated Machine Learning Engineer / Data Scientist to design, build, and deploy innovative models and solutions.
- Collaborate with cross functional teams to turn complex datasets into actionable insights and build ML solutions that drive business value.
Key Responsibilities
- Model Development: Design, train, and evaluate machine learning models for classification, regression, clustering, and recommendation.
- Data Preparation: Work with large and complex datasets, performing data cleaning, preprocessing, and feature engineering.
- 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.
- Collaboration: Collaborate with data engineering teams to build data pipelines.
- Visualization and Reporting: Create clear and actionable visualizations and reports.
- Monitoring and Maintenance: Monitor model performance in production, address drift or bias issues, and optimize models.
- Tool Development: Build tools and frameworks to enable rapid experimentation and iteration.
- 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 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 NLP, computer vision, or time series analysis is a plus.
Soft Skills
- Strong problem solving and analytical thinking abilities.
- Excellent communication skills, with 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 latest advancements in ML and AI.
About The Company
- Datamaze is a dynamic company specializing in AI, Data, and Analytics consulting services.
- Offers services including data strategy development, AI model creation, advanced analytics, and data visualization.
- Client centric approach focusing on customized solutions for unique business challenges.
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