• Develop, train, and optimize machine learning models for various mobile app features. • Research and implement state-of-the-art AI techniques to improve user engagement and app performance. • Collaborate with cross-functional teams to integrate AI-driven solutions into our applications. • Design and maintain scalable ML pipelines, ensuring efficient model deployment and monitoring. • Analyze large datasets to derive insights and drive data-driven decision-making. • Stay updated with the latest AI trends and best practices, incorporating them into our development processes. • Optimize AI models for mobile environments to ensure high performance and low latency.

Role Description We are looking for a hard working and diligent team member to join our business. Your role will be to manage a small number of vending machines that are located within: - Motorway Services - Shopping Centres - Car Parks - Other sites As well as managing the vending machine units and ensuring they are fully operational and working properly, you will be responsible for: - Maintaining healthy stock levels - Liaising with head office for stock replenishment The role will involve visiting the sites on an adhoc basis and replenishing them when required. Full training will be provided. Access to OWN VEHICLE is essential. This role would be ideal for a retired/semi-retired individual or someone who is looking for some extra income without too much stress! We envisage around 5-10 days work per month initially. Qualifications - Access to own vehicle - Ideal for retired/semi-retired individuals - Looking for extra income Requirements - Hard working and diligent - Ability to manage vending machines - Willingness to visit sites on an adhoc basis Benefits - Full training provided - Flexible working days (5-10 days per month)

Role Description As a Senior Machine Learning Engineer, you will be responsible for designing, developing, and maintaining high-quality software solutions. You will collaborate with cross-functional teams to understand business requirements and translate them into scalable and efficient software applications. Your role will involve leading technical projects, mentoring junior engineers, and continuously improving software development practices to ensure the delivery of robust and reliable software systems. Responsibilities and Duties - Design, build, and deploy scalable machine learning models and pipelines across the full ML lifecycle; - Develop and optimize data processing workflows using Python, SQL, and distributed frameworks such as PySpark; - Deploy and monitor machine learning models in cloud environments, ensuring performance, reliability, and scalability; - Collaborate with cross-functional teams to translate business problems into data-driven solutions and improve model performance. Qualifications - Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field, or equivalent practical experience; - Experience as a Machine Learning Engineer with a focus on deploying and scaling ML systems; - Strong proficiency in Python, SQL, and PySpark for large-scale data processing; - Hands-on experience with machine learning frameworks such as scikit-learn, TensorFlow, PyTorch, or XGBoost; - Experience designing and managing end-to-end ML pipelines using tools such as MLflow or similar; - Experience deploying models in cloud platforms such as AWS, GCP, Azure, or Databricks; - Strong understanding of MLOps practices including CI/CD, model versioning, and automated retraining; - Experience working with containerized environments and Kubernetes for ML workloads; - Ability to design evaluation metrics and validate model performance effectively; - Strong communication and collaboration skills to work with cross-functional teams and stakeholders. Company Description Encora is the preferred digital engineering and modernization partner of some of the world’s leading enterprises and digital native companies. With over 9,000 experts in 47+ offices and innovation labs worldwide, Encora’s technology practices include Product Engineering & Development, Cloud Services, Quality Engineering, DevSecOps, Data & Analytics, Digital Experience, Cybersecurity, and AI & LLM Engineering. At Encora, we hire professionals based solely on their skills and qualifications, and do not discriminate based on age, disability, religion, gender, sexual orientation, socioeconomic status, or nationality.

Role Description Fetch is building the future of personalized consumer experiences. We’re looking for a Staff Machine Learning Engineer to serve as the technical lead for a high-impact ML team focused on personalization, relevance, and ranking. In this role, you will own the technical direction and execution for your team’s ML systems - driving high-quality architecture, guiding implementation, and ensuring models and infrastructure operate reliably at scale. You’ll partner closely with product and cross-functional stakeholders while remaining deeply hands-on in design and development. Responsibilities - Serve as the technical lead for a single ML-focused team, setting direction and raising the bar on engineering quality and system design. - Design, build, and scale ML systems supporting personalization, ranking, search, or ad-related use cases. - Own end-to-end architecture for your team’s services, including model training, evaluation, deployment, and serving. - Drive clarity in ambiguous problem spaces, translating product needs into scalable technical solutions. - Lead design reviews and ensure thoughtful tradeoffs around latency, reliability, experimentation, and maintainability. - Partner closely with product, data, and engineering stakeholders to deliver measurable business impact. - Mentor engineers through hands-on technical guidance, feedback, and example. - Use AI tools to accelerate development and improve system design, including: - Prototyping and validating ideas with LLM tools. - Leveraging AI for code iteration and experimentation. - Using AI assistants for architecture diagramming and design validation. - Exploring LLM-powered features where appropriate. Qualifications - 5+ years of industry experience in machine learning or software engineering, with demonstrated ownership of production ML systems operating at scale. - Proven experience building and scaling ML systems in personalization, relevance, search, or ad tech domains. - Strong hands-on expertise in distributed systems, data pipelines, and ML infrastructure. - Experience deploying ML models into production and operating them at consumer scale. - Demonstrated ownership of complex technical initiatives within a team. - Strong systems design skills with the ability to clearly articulate tradeoffs and implementation decisions. - Experience mentoring engineers and influencing technical standards within a team. - Ability to operate effectively in ambiguous environments and drive projects to completion. Preferred Requirements - Familiarity with LLMs and their application in personalization, feature generation, or search. - Experience with real-time or streaming ML systems. - Exposure to experimentation frameworks (A/B testing) and model performance measurement. - Experience bridging model development with real-time serving systems.