Machine Learning Specialist
8 hours ago
At Burq, we believe that technology has the power to transform industries and create new opportunities. As a leader in the delivery space, we are committed to harnessing the latest advancements in AI and machine learning to drive innovation and growth.
Our team of experts is dedicated to designing and developing cutting-edge solutions that help businesses streamline their operations, enhance customer experiences, and stay ahead of the competition. If you are passionate about leveraging technology to drive business success, we invite you to join our team.
As an AI/ML Engineer at Burq, you will play a critical role in shaping the future of our company. You will be responsible for designing, developing, and deploying machine learning models and data pipelines that drive impactful business decisions. Your expertise in data engineering, machine learning, and cloud technologies will be essential in managing our data infrastructure and delivering high-quality AI/ML projects.
Key Responsibilities:
Job Summary:
The AI/ML Engineer will design, develop, and deploy machine learning models and data pipelines to drive business growth and improve operational efficiency.
Key Responsibilities:
1. Design, develop, and deploy machine learning models using Databricks and Apache Spark
2. Implement data preprocessing, feature engineering, and model training pipelines
3. Utilize dbt (data build tool) to transform and model data in Snowflake to prepare datasets for machine learning
4. Use SQL and Python to analyze large datasets, derive meaningful insights, and build training datasets
5. Conduct exploratory data analysis to identify trends, patterns, and anomalies
6. Develop and maintain ETL pipelines using Airbyte to ingest data from various sources into Snowflake
7. Manage and optimize data storage and retrieval using Delta Lake on Databricks to ensure efficient access for ML models
8. Create and maintain interactive dashboards and visualizations in Tableau to communicate model results and insights to stakeholders
9. Collaborate with data scientists to refine and improve machine learning models
10. Monitor and evaluate the performance of deployed models, ensuring they meet accuracy and performance standards
11. Work with relational databases such as MySQL and PostgreSQL for data storage and management as needed
12. Communicate complex technical concepts and results to non-technical stakeholders effectively
Requirements:
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related field
- Proficiency in SQL and Python
- Experience with data integration tools like Airbyte
- Strong knowledge of data warehousing concepts and hands-on experience with Snowflake
- Experience with data transformation tools such as dbt
- Proficiency in using Databricks and Apache Spark for big data processing and machine learning
- Familiarity with Delta Lake for data lake management
- Experience with data visualization tools like Tableau
- Experience with relational databases like MySQL and PostgreSQL
- Strong analytical and problem-solving skills
- Excellent communication and teamwork abilities
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