Data Engineer

An early-stage startup active in the data science and machine learning engineering space is looking for a Data Engineer. The engineer will work on client deliverables to develop machine learning models that efficiently solve business problems. The company aims at being at the forefront of technologies and AI that will shape the future, including the simultaneous adoption of algorithms, engineering, and others. The selected candidate will utilize great problem-solving and prototyping skills while partnering with engineers and communicating recommendations and solutions that meaningfully impact the systems. This role requires a time overlap with IST. 

Job Responsibilities:

• Design scalable overarching solution frameworks
• Carry out exploratory and statistical analysis to discover primary insights
• Create and tune high-performance models, test accuracy and importance of model predictions
• Work actively with feature engineering to iterate and improve on the model efficiency
• Collaborate with other team members to productionalize models and assist with developing pipelines for inference and feature gathering
• Track model performance and critical business metrics through excellently designed dashboards
• Be responsible for models in production, fix bugs concerned with the data and feature leakage
• Align projects with deadlines without compromising on deliverables or quality

Job Requirements:

• Bachelor’s/Master’s degree in Engineering, Computer Science (or equivalent experience)
• At least 3+ years of relevant data engineering experience 
• Must have hands-on experience with distributed systems
• Nice to have some experience in building and productionizing machine and deep learning pipelines on cloud platforms like AWS, Azure, AWS Solutions Architecture, and GCP 
• Expertise with technologies like PySpark, Apache Kafka, Kafka, Spark, Apache Spark, and Scala is a plus