ML Engineer

Your Role:

• Communicate with the Product and Management teams to understand business requirements and user problems
• Carry out EDA in collaboration with the Analytics team to identify solutions and research industry best practices and tools for its implementation
• Build data ingestion pipelines, models and serving layers, and deploy them by working closely with the Tech team
• Communicate the solutions’ business impact, caveats and implementation deadlines to all stakeholders
• Broadly 60%-70% of time dedicated to Model Deployment work-streams and rest to Model Development

Must Haves:

• 3-5 years experience in developing, delivering and maintaining data-driven solutions  (Ex: recommendation systems, traffic forecasting, dynamic pricing, video and text processing)
• Good understanding of fundamental statistics and ML concepts (Ex: hypothesis testing, linear and ensemble models, graph analytics, deep learning)
• Expert-level grasp on Python programming language and SQL (Ex: OOPs, async-await paradigm, CTEs, window functions)
• Hands-on experience with creating data ingestion pipelines and APIs that serve model results at scale (Ex: Spark, FastAPI, Celery)
• Ability to break down business requirements into technical problems and communicate solutions to other teams

Good to Haves:

• Bachelor's degree in a quantitative discipline - Engineering, Statistics, Mathematics, Economics etc.
• Ability to identify and integrate innovative tools which can help build more efficient solutions
• Love for sports
• Experience building NLP and computer vision applications
• Data visualization skills