Senior ML Engineer

About the Role

Join Snoonu as a Senior Machine Learning Engineer, contributing to the development and deployment of cutting-edge machine learning and optimization algorithms that enable the coordination of human couriers, robots, and drones within a hybrid autonomous logistics framework.

Primary Responsibilities

• Create and deploy algorithms that optimize task assignment, routing, scheduling, and dispatch across a multi-agent fleet.
• Design and refine multi-agent reinforcement learning models to enhance fleet coordination amidst fluctuating demand and traffic scenarios.
• Build forecasting models for demand and spatiotemporal predictions using state-of-the-art techniques such as Transformers and graph-based methods to ensure proactive resource allocation.
• Develop optimization models that consider energy and environmental factors to maximize battery efficiency, manage charging plans, sequence deliveries, and boost operational effectiveness in Qatar’s climate.
• Collaborate with backend and platform engineers to integrate ML models into the Robotics-as-a-Service orchestration platform, ensuring high reliability and low latency.
• Assess the effectiveness of models through metrics like routing efficiency, ETA accuracy, fleet latency, and energy consumption supporting technology readiness and pilot tests.
• Implement thorough experimentation workflows including offline benchmarking, simulations, and controlled pilot trials to enhance model robustness.
• Manage continuous learning systems addressing monitoring, retraining, and drift mitigation for models using live operational data.
• Document all aspects of model design, experimentation, validation, and assumptions for internal reporting and stakeholder communication.

Required Qualifications and Skills

• Bachelor’s or Master’s degree in Machine Learning, AI, Computer Science, Data Science, Operations Research, or related disciplines; PhD preferred for research-focused roles.
• 2 to 4 years of backend development experience with in-depth Python and C++ skills.
• Solid analytical capabilities to solve complex robotics-related challenges.
• Research mindset focused on translating experimental outcomes into deployable autonomy improvements.
• Effective collaborator within multidisciplinary teams including robotics and operations.
• Strong communication skills to convey technical details and validation results clearly.
• High accountability and ownership over project delivery, quality, and timelines.
• Adaptability to fast paced R&D settings with iterative prototyping and testing.
• Good understanding of operational business contexts and ability to convert requirements into technical solutions.
• Receptive to constructive feedback and eager to incorporate suggestions from senior technical staff.

Technical Expertise

• Proficiency in Python with solid grasp of object-oriented design, design patterns, and maintaining clean code.
• Experience developing backend services using frameworks like FastAPI, Flask, or Django.
• Ability to build and maintain RESTful APIs with thorough error handling and logging functionality.
• Expertise in AWS cloud services including Lambda, SQS/SNS, API Gateway, Step Functions, DynamoDB, RDS, S3, and CloudWatch.
• Designing event-driven and serverless cloud architecture.
• Knowledge of AWS IAM, environment setups, and adhering to cloud security best practices.
• Experience in embedded systems leveraging Python and deep learning frameworks.
• Hands-on work with reinforcement learning (RL) and multi-agent reinforcement learning (MARL).
• Development of optimization and decision systems for routing, scheduling, and dispatch.
• Time-series forecasting and spatiotemporal modeling expertise.
• Use of Graph Neural Networks (GNNs) for mobility and routing challenges.
• Applying energy optimization and predictive control methods including MPC and hybrid ML/control approaches.
• Strong background in evaluation methods such as metric design, baseline comparisons, A/B testing, and both offline and online validation.
• Working knowledge with large datasets, feature engineering, and practical model deployment considerations.
• Familiarity with simulation platforms, digital twins, or synthetic data creation is advantageous.
• Awareness of real-time systems, stream processing, and ML model monitoring techniques offers an edge.
• Experience related to logistics, last-mile delivery, fleet routing, or mobility analytics is highly valued.

Company Overview and Culture

Snoonu is a pioneering Qatari Super App that blends fast delivery, ride-hailing, and shopping into one platform. Driven by technology and a global team, the company is redefining daily convenience.

Core values emphasized include customer obsession, integrity, curiosity and creativity, leadership through ownership, efficient work practices, strong teamwork, and turning ideas into reality.

Perks and Work Environment

• Fully remote work with collaboration across international teams.
• Professional development support including learning budgets and resource access.
• High autonomy with ownership of assigned projects.
• Generous and flexible time off policies promoting wellness.
• Agile methodologies embedded throughout the organization.

Diversity and Social Responsibility

Snoonu is an equal opportunity employer committed to sustainability and social contribution. The company integrates eco-friendly operations and community engagement initiatives into its business model, fostering inclusivity and diversity.

Join Us

This opportunity invites skilled engineers to shape technological innovation, be part of a supportive team, and grow professionally in a forward-thinking environment.