Marketplace Company - AI/ML Expert

We are looking for a seasoned AI/ML Expert with a strong background in data architecture, machine learning pipelines, and AI-driven dashboards. This role is ideal for someone who enjoys designing scalable data systems and transforming raw data into actionable insights through intelligent visualizations. You will be instrumental in laying the foundational data infrastructure and building cutting-edge ML-driven dashboards to support data-informed decision-making across the organization.

Key Responsibilities

Data Infrastructure & Architecture

- Design and implement robust, scalable data structures to support high-throughput ML workloads.

- Build and manage data pipelines using modern data engineering tools and frameworks.

- Ensure data governance, quality, lineage, and security across the data stack.

Machine Learning Solutions

- Develop and deploy end-to-end ML models for predictive analytics, personalization, recommendation systems, anomaly detection, etc.

- Integrate ML models into production environments with monitoring and retraining pipelines.

- Drive experimentation and continuously improve model performance using MLOps best practices.

AI-Powered Dashboards

- Create intuitive, real-time dashboards and analytical tools powered by ML insights.

- Collaborate with business stakeholders, and data analysts to understand use cases and deliver impactful visualizations.

- Leverage technologies like Python, Tableau, or custom front-end dashboards powered by APIs.

Required Qualifications

- 8-10 years of total experience in data science, ML engineering, or AI systems design.

- Proven expertise in data architecture, data modeling, and machine learning workflows.

- Experience with data pipelines (Airflow, Prefect, etc.), data warehouses (Snowflake, Redshift, BigQuery), and cloud platforms (AWS, GCP, or Azure).

- Hands-on experience with BI tools (Power BI, Tableau, Looker) and/or custom AI dashboards (Streamlit, Dash, React-based).

- Ability to translate business needs into technical solutions and communicate effectively with both technical and non-technical audiences.