Tech Lead – Logistics Systems

Overview

Join the cutting-edge team at Snoonu, Qatar's homegrown Super App, as a Tech Lead specializing in logistics-focused AI/ML and Python backend systems. You will spearhead a cross-functional engineering group developing sophisticated AI/ML services and data platforms, driving innovation to transform daily life in the region through technology.

Key Responsibilities

• Lead and mentor a diverse engineering team consisting of Senior, Middle, and Junior engineers to meet software and machine learning goals.
• Collaborate closely with Product, Data Science, QA, DevOps, and Platform teams to ensure smooth delivery of AI/ML projects.
• Architect and design scalable AI/ML applications, model-serving solutions, and backend Python services ensuring high performance and reliability.
• Establish standards for feature engineering pipelines, data ingestion, and integration with machine learning operations platforms.
• Transform complex AI/ML initiatives into manageable engineering tasks and technical roadmaps.
• Partner with Data Scientists to deploy ML models into production, focusing on reproducibility, versioning, and monitoring.
• Implement and manage model serving frameworks, vector databases, and inference optimization techniques.
• Improve development processes including CI/CD and ML lifecycle automation, while upholding coding standards and reducing technical debt.
• Assist recruitment efforts for backend and ML engineering roles, promote knowledge sharing, and cultivate a strong collaborative team culture.
• Oversee incident management and reliability, tackling model drift, data quality issues, and performance monitoring.

Required Qualifications and Skills

• Bachelor's degree in Computer Science, Engineering, Data Science, or a closely related discipline.
• Experience in logistics solutions or closely related industries is essential.
• Advanced degrees in AI/ML or Applied Data Science (MSc/PhD) are advantageous.
• Exceptional communicator capable of articulating intricate ML processes and architectural decisions to diverse stakeholders.
• Strong data-driven mindset to support decisions with measurable metrics.
• Balanced leadership skills combining delegation and hands-on technical expertise in Python backend and ML system design.
• Comfort navigating ambiguous situations and aligning teams around AI-focused product goals.

Technical Expertise

• Expert-level proficiency in Python with strong command of backend frameworks such as FastAPI, Flask, or Django and experience with microservices architecture.
• Solid foundation in algorithms, distributed systems, and scalable backend solutions.
• Experience deploying machine learning models into production environments across batch, real-time, and streaming systems.
• Familiarity with ML frameworks like TensorFlow, PyTorch, Scikit-learn, and model serving tools such as TorchServe, MLflow, SageMaker, or Vertex AI.
• Hands-on with vector databases, feature stores, embedding-based search technologies.
• Proficient with CI/CD pipelines tailored for ML, containerization (Docker), orchestration, and cloud platforms including AWS or GCP.
• Knowledgeable about monitoring tools for ML workflows, including logging, metrics, tracing, and detecting model drift.
• Strong understanding of data pipeline architectures, ETL/ELT processes, and various database types (relational and NoSQL).
• Experience designing caching, queuing, and event-driven architectures supporting ML workloads.
• Established testing standards for data validation, model accuracy, API reliability, and system performance with emphasis on observability and monitoring of AI services.

Culture and Values

Snoonu prides itself on a customer-obsessed, ethical, innovative, and collaborative environment that values ownership, efficiency, and diversity. The company offers a globally minded workplace where employees are encouraged to grow and contribute to transformative technological innovations.

Benefits and Work Environment

• Engagement with an international team and exposure to global practices.
• Learning budgets and access to educational resources to foster professional development.
• Autonomy in task ownership and career path within an agile framework.
• Flexible and generous leave policies supporting work-life balance and wellness.
• Certified Great Place to Work®, with ISO 9001:2015 and ISO 45001:2018 standards emphasizing quality and safety.
• Commitment to sustainability, corporate social responsibility, and community engagement.
• Inclusive workplace promoting fairness and equal opportunity across all backgrounds.