Qualifications

• 10+ years in software engineering or data science, with 5+ years specializing in AI/ML at enterprise scale.
• Proven expertise in machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) and MLOps tools (MLflow, Kubeflow).
• Strong background in data pipelines, feature engineering, and large-scale training/inference systems.
• Experience deploying models in cloud-native environments (Azure, AWS, or GCP).
• Knowledge of streaming architectures (Kafka, Flink, Spark Streaming) for real-time ML applications.
• Ability to influence executives and guide engineering teams in adopting AI/ML.
• Excellent communication skills to explain complex AI concepts to technical and non-technical stakeholders.

Responsibilities

• Define the enterprise AI/ML roadmap, aligning business goals with technical execution.
• Build scalable ML models for anomaly detection, forecasting, optimization, and intelligent automation.
• Establish robust pipelines for training, deployment, monitoring, and continuous improvement of models.
• Partner with backend, data engineering, and product teams to embed AI into applications, APIs, and workflows.
• Collaborate with data engineering to ensure high-quality, governed, and lineage-tracked datasets for ML use.
• Drive AI-enabled product features such as loss-prevention intelligence, predictive analytics, and insights-as-a-service.
• Guide engineers in AI/ML best practices, reusable frameworks, and responsible AI principles.

Benefits

• Office hybrid work model providing flexibility.
• Opportunities for mentorship and professional growth.
• Involvement in impactful AI initiatives across the organization.