Responsibilities:
Design, implement, and improve ML and AI models to drive business outcomes across multiple domains, such as recommendation systems, image recognition, ChatBot, etc.
Own the end-to-end ML lifecycle: data preprocessing, feature engineering, model training, validation, and deployment.
Expert level in designing evaluation pipelines to prove performance, scalability, and consistency
Leverage generative AI and LLMs to enhance existing workflows and explore new product opportunities.
Collaborate with Product, Engineering, and Analytics teams to align modeling efforts with business needs.
Clearly communicate complex findings and model insights to stakeholders.
Design, implement, and improve ML and AI models to drive business outcomes across multiple domains, such as recommendation systems, image recognition, ChatBot, etc.
Own the end-to-end ML lifecycle: data preprocessing, feature engineering, model training, validation, and deployment.
Expert level in designing evaluation pipelines to prove performance, scalability, and consistency
Leverage generative AI and LLMs to enhance existing workflows and explore new product opportunities.
Collaborate with Product, Engineering, and Analytics teams to align modeling efforts with business needs.
Clearly communicate complex findings and model insights to stakeholders.
Requirements:
Requirements
BSc or higher in Computer Science, Mathematics, Statistics, or related fields.
4+ years of hands-on experience as a Data Scientist, ideally within mobile, gaming, or social network industries.
Proven experience with AI/ML frameworks and toolkits (Scikit-learn, TensorFlow, PyTorch, LangChain, etc.).
Familiarity with MLOps best practices, model versioning, experiment tracking, and continuous deployment.
Strong knowledge of machine learning techniques: Classification, regression, segmentation, reranking, model interpretability.
Solid background in data analysis and statistics; ability to design experiments and interpret results.
Experience working in cloud environments, especially Google Cloud Platform (GCP) – BigQuery, GCS, Vertex AI (a plus).
Comfortable working in fast-paced, production-critical environments with a sense of ownership and accountability.
Requirements
BSc or higher in Computer Science, Mathematics, Statistics, or related fields.
4+ years of hands-on experience as a Data Scientist, ideally within mobile, gaming, or social network industries.
Proven experience with AI/ML frameworks and toolkits (Scikit-learn, TensorFlow, PyTorch, LangChain, etc.).
Familiarity with MLOps best practices, model versioning, experiment tracking, and continuous deployment.
Strong knowledge of machine learning techniques: Classification, regression, segmentation, reranking, model interpretability.
Solid background in data analysis and statistics; ability to design experiments and interpret results.
Experience working in cloud environments, especially Google Cloud Platform (GCP) – BigQuery, GCS, Vertex AI (a plus).
Comfortable working in fast-paced, production-critical environments with a sense of ownership and accountability.
Advantages:
Experience developing recommendation engines, especially with deep learning and reranking techniques.
Experience with LLM-based applications, prompt engineering, Agents development, etc.
This position is open to all candidates.
