AhaMove

7/28 Thanh Thai, TP Hồ Chí Minh

Quy mô công ty : 100-499

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Tóm lược

AhaMove

Design, develop, and deploy machine learning models for recommendation systems, personalization, forecasting, ranking, and user behavior analysis.
Build and optimize end-to-end AI pipelines from data ingestion, feature engineering, model training, evaluation, deployment, and monitoring.
Train and fine-tune machine learning models on cloud platforms for large-scale predictive modeling tasks.
Work with large-scale datasets using Databricks, Spark, and distributed data processing frameworks.
Develop LLM-powered applications using modern frameworks such as LangChain, tool calling, RAG pipelines, vector databases, and agent workflows.
Work with structured and unstructured datasets including transactional data, logs, documents, and user interaction data.
Collaborate with product managers and engineering teams to translate business problems into scalable AI solutions.
Optimize model inference, retrieval performance, latency, and production reliability.
Conduct experimentation, A/B testing, and performance analysis to improve business KPIs.
Design and implement robust model evaluation frameworks including offline evaluation, online A/B testing, and business KPI measurement.
Monitor model drift, prediction quality, and production performance to ensure long-term model reliability.
Stay up to date with advances in machine learning, generative AI, recommendation systems, and MLOps technologies.

Physical Wellbeing Benefit: General Insurance, Medical check-up, Accident Insurance, Healthcare Insurance.
Emotional Wellbeing Benefit: Company Trip, Year End Party, Aha Hour Activities, Special Day Gifts, Aha Club (Badminton, Soccer).
Financial Wellbeing Benefit: Grab/Be For Work (Tech/Lead Level), Workplace Relocation, 13th Month Salary, PP Appreciate, Annual Leave Remain.

4+ years of experience in Data Science, Machine Learning, or AI Engineering roles.
Strong proficiency in Python and SQL.
Experience training and deploying machine learning models on cloud platforms such as AWS, GCP, or Azure.
Experience working with Databricks, Spark, or distributed computing environments for large-scale data processing.
Strong understanding of recommendation systems, ranking models, clustering, classification, and predictive modeling.
Experience working with LLM applications, RAG systems, vector databases, embeddings, and prompt engineering.
Experience evaluating predictive models, recommendation systems, ranking systems and LLM applications using both offline and online metrics.
Familiarity with LangChain, LangGraph, or similar GenAI frameworks.
Experience with cloud platforms such as AWS, GCP, or Azure.
Experience with containerization and orchestration tools such as Docker and Kubernetes is a plus.
Strong analytical thinking and ability to work cross-functionally in a fast-paced environment.
Good communication skills in both technical and business contexts.

Nice to Have

Experience with logistics, e-commerce, or marketplace platforms.
Experience with recommendation systems for user personalization or ranking optimization.
Familiarity with Airflow, BigQuery, MLflow, feature stores, or MLOps workflows.
Experience monitoring production ML systems and optimizing model performance at scale.
Knowledge of experimentation frameworks and online evaluation metrics.