Role Overview

Lead the design, development, and deployment of advanced machine learning and AI systems that drive measurable business impact. As a senior technical leader, you will define strategy, guide teams, and architect scalable, production-ready models that power innovation across the organization.

Key Responsibilities

• Strategic Leadership: Define and execute the company’s data science and AI roadmap. Provide direction on model development, deployment, and long-term AI capability building.

• Model Development: Architect and deliver predictive, generative, and prescriptive models using advanced machine learning and deep learning techniques.

• AI Platform Engineering: Oversee end-to-end ML pipelines, from data collection and preprocessing to deployment and monitoring in production environments.

• Data Architecture: Ensure data integrity, scalability, and reproducibility across large and complex datasets.

• Mentorship: Build and mentor a high-performing team of data scientists and ML engineers. Promote best practices in experimentation, validation, and continuous learning.

• Innovation: Explore and apply emerging AI methods such as large language models (LLMs), multimodal learning, and reinforcement learning to real-world business problems.

• Stakeholder Engagement: Present analytical insights and model outcomes clearly and persuasively to technical and executive audiences.

Qualifications

• Education: Master’s or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related quantitative field.

• Experience: 10+ years in data science, AI, or applied ML, including 3+ years in a senior or staff-level role leading impactful, production-level AI initiatives.

Required Technical Skills

• Expert proficiency in Python and frameworks such as TensorFlow, PyTorch, and scikit-learn.

• Strong foundation in statistical modeling, feature engineering, and end-to-end ML pipeline design.

• Proficiency in SQL and experience with data pipeline orchestration (Airflow, Dataflow, Kubeflow).

• Deep understanding of MLOps, including CI/CD for ML, model serving, and monitoring.

• Familiarity with big data technologies (Spark, Hadoop) and data visualization tools (Tableau, Power BI, Matplotlib).

• Preference for experience or certification with Google Cloud Platform (GCP), including BigQuery, Vertex AI, and Dataflow.

✔ Fully remote & flexible work culture
✔ Competitive compensation & benefits
✔ Career growth and learning opportunities
✔ Collaborative, innovative, and fast-growing environment

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