Wild.Codes

About the client

• Industry: Fashion / retail e-commerce

• Product: Shopify-based online store combined with physical retail stores (Shopify POS)

• Markets: GCC region (multi-region setup, primary focus on Kuwait)

• Team: Lean internal team, close collaboration with non-tech COO and CEO

Who we’re looking for
 

A hands-on Shopify Developer with experience in store administration and day-to-day operations, who can own the Shopify platform end-to-end and act as the technical point of responsibility.

Requirements:

• 3+ years of hands-on experience developing, customizing, and maintaining Shopify stores

• Practical experience working with Shopify themes, Liquid, sections, and store configuration

• Experience with Shopify POS and multi-region setups (strong plus)

• Hands-on experience with inventory syncing, product uploads, and logistics integrations

• Strong experience working with Shopify apps, plugins, and analytics tools

• Ability to troubleshoot issues at the theme, app, or platform level

• Comfortable working directly with non-technical CEO / COO and taking ownership

• Clear communication skills (English)

• Background in fashion or retail e-commerce is a strong plus

Responsibilities:

Shopify Platform Ownership

• Own the Shopify store from a technical perspective, ensuring stability and performance

• Implement theme-level changes, page updates, and configuration improvements

• Maintain and optimize store structure, collections, and product presentation

Daily Store Administration

• Upload and manage products and collections according to the product catalogue

• Monitor inventory levels and automate low-stock and out-of-stock alerts

• Ensure the store is always up-to-date and operational

Multi-Region & Shopify POS

• Support and maintain Shopify POS across physical retail locations

• Manage inventory syncing and separation between online and POS inventory

• Handle multi-currency, tax, and regional configuration challenges across GCC markets, working within Shopify’s platform limitations

• Coordinate logistics and courier integrations for order fulfillment

Apps, Integrations & Technical Maintenance

• Install, configure, and maintain third-party Shopify apps and plugins

• Recommend and evaluate new tools to improve store operations and performance

• Troubleshoot checkout issues, app conflicts, and platform inconsistencies

• Act as the main technical contact with Shopify support and third-party vendors

Analytics & Reporting

• Set up and maintain analytics and tracking tools (Google Analytics, Meta Pixel, Hotjar, etc.)

• Monitor key metrics such as conversion rate, cart abandonment, and top-selling products

• Share regular performance insights with management

Cross-Team Collaboration

• Work closely with Marketing on homepage updates, promotions, and campaigns

• Coordinate with Customer Support to ensure product data accuracy

• Escalate issues to relevant internal teams when needed

• Coordinate with translators for Arabic content when required

Location: Remote

Working timezone: Toronto / North America overlap (afternoon → late evening EU time);
Engagement: Full-time, long-term

We’re looking for a versatile and hands-on Machine Learning Engineer to join our client's team and take ownership of ML systems from early research through to real-world deployment. In this role, you’ll work across the full lifecycle - shaping datasets, exploring new approaches, building models, and running them reliably in production. T

his is a good fit if you enjoy fast iteration, practical experimentation, and seeing your work directly influence product outcomes.

Responsibilities:

• ML solution design: Explore, evaluate, and implement machine learning approaches to solve complex product and business challenges using modern model architectures.
• Experimentation workflows: Set up and maintain pipelines that support fast prototyping, testing ideas, and validating assumptions.
• Structured experimentation: Plan, run, and document experiments in a reproducible way, including tuning hyperparameters, comparing architectures, and testing data variants using tools like MLflow or Weights & Biases.
• Production rollout: Bring models into production using established CI/CD workflows and model serving infrastructure.
• Model observability: Build monitoring and alerting around deployed models to track accuracy, drift, latency, and overall system health.
• Inference optimization: Improve runtime performance and cost efficiency through techniques such as quantization, pruning, and distillation.
• Training data ownership: Create, refine, and maintain high-quality datasets, including data augmentation and curation strategies.
• Modern ML methods: Keep up with current advances in the field and apply state-of-the-art approaches, particularly in the area of large language models.

Requirements:

• 3+ years of hands-on experience building and deploying machine learning models in production systems.
• Strong Python skills and experience writing production-grade ML code.
• Solid experience with deep learning frameworks, especially PyTorch.
• Practical background in hyperparameter tuning and optimization using tools such as Optuna or Ray Tune.
• A disciplined approach to experimentation, with strong habits around reproducibility and tracking.
• Hands-on work with LLMs, including fine-tuning, prompt design, retrieval-augmented generation, and efficient inference.
• Experience applying model optimization techniques (e.g. quantization, pruning).
• Proven ability to design and build datasets rather than only consuming existing ones.
• Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a closely related field.

Nice to have:

• Experience with advanced architectures such as Transformers or Mixture-of-Experts models.
• Contributions to open-source projects or personal ML projects that demonstrate curiosity and depth.
• Practical understanding of end-to-end MLOps, including tools like Docker, Kubernetes, MLflow, Kubeflow, or Prometheus.