• Design, train and improve upon cutting-edge models. • Help us develop new techniques to train and serve models safer, better, and faster. • Train extremely large-scale models on massive datasets. • Explore continual and active learning strategies for streaming data. • Learn from experienced senior machine learning technical staff. • Work closely with product teams to develop solutions.

• Design, implement, and maintain reliable, scalable, and secure infrastructure, applications, and tooling, with a focus on our ML/AI pipelines and workloads • Write clean, maintainable code, and perform peer code-reviews • Write clear and concise documentation and engage in cross-team communication and knowledge sharing • Work with other team members to investigate design approaches, prototype new technology and evaluate technical feasibility • Pair with adjacent teams to understand how your frameworks and infrastructure are actually used in the field, continuously improving them and leveraging recent advances to improve developer velocity

Role Description We are seeking a highly skilled Machine Learning Engineer with strong experience in Supply Chain, Transportation, and Delivery Analytics to support the design and development of predictive transportation delivery models. This role will focus on translating complex operational processes into scalable machine learning solutions that improve delivery efficiency, forecasting accuracy, and business decision-making. The ideal candidate combines deep Data Science expertise with practical ML Engineering capabilities, including model experimentation, feature engineering, and production deployment using Google Vertex AI. Key Responsibilities - Machine Learning Model Development - Design, train, test, and optimize machine learning models focused on transportation and delivery use cases. - Develop predictive models primarily using XGBoost and related ML techniques. - Perform feature engineering, feature selection, and experiment design to improve model performance and business outcomes. - Evaluate model accuracy, robustness, and operational impact using appropriate statistical and ML metrics. - Supply Chain & Transportation Analytics - Analyze transportation and logistics workflows to identify optimization opportunities. - Collaborate with business stakeholders to understand operational processes, delivery constraints, and performance drivers. - Translate business requirements into scalable data science and ML solutions. - Data Exploration & Engineering - Conduct exploratory data analysis (EDA) on large operational and logistics datasets. - Partner with data engineering teams to ensure reliable data ingestion, transformation, and feature availability. - Ensure data quality, consistency, and readiness for model development. - ML Engineering & Deployment - Deploy and operationalize ML models using Google Vertex AI. - Support the implementation of scalable ML pipelines and MLOps best practices. - Collaborate with engineering teams to integrate models into production systems and business workflows. - Collaboration & Leadership - Work closely with cross-functional teams including Supply Chain, Operations, Data Engineering, and Product teams. - Provide technical guidance on model design, experimentation, and deployment strategies. - Document methodologies, findings, and implementation approaches clearly for both technical and business audiences. Qualifications - 7+ years of experience in Machine Learning, Data Science, or Advanced Analytics roles. - Strong hands-on experience building predictive models using XGBoost or similar gradient boosting frameworks. - Experience in Supply Chain, Transportation, Logistics, or Delivery Analytics. - Strong expertise in: - Data exploration and feature engineering - Experiment design and model evaluation - Statistical analysis and predictive modeling - Proficiency in Python and SQL for ML development and data analysis. - Experience deploying ML solutions using Google Vertex AI or similar cloud ML platforms. - Strong understanding of the end-to-end ML lifecycle and MLOps concepts. - Ability to communicate effectively with both technical and business stakeholders. - Familiarity with cloud platforms such as GCP, AWS, or Azure. - English – Advanced (required). Benefits - Statutory & Major benefits - Personal Growth - Competitive salary - Attractive benefits plan Company Description NEORIS is a Digital accelerator that helps companies enter the future, having 20 years of experience as Digital Partners of some of the largest companies in the world. We have more than 4,000 professionals in 11 countries, with our multicultural startup culture where we cultivate innovation, continuous learning to create high-value solutions for our clients.

Role Description In our newly created Head of Leadership, Learning and Experience role, you'll develop and mobilise a plan to enhance the capability and culture of our business, driving the engagement, performance and contribution of our workforce. - Priority focus on leadership capability, skills development and people experience initiatives such as equality, diversity and inclusion, wellbeing, induction and recognition and appreciation. - Lead a small and expert team to deliver against our strategic and operational priorities. - Pivotal leadership role influencing and impacting the capability and commitment of our employed and self-employed teams to maximise business success. Qualifications - Proven experience in leading, designing, and delivering leadership and skills development programmes across operational, multi-site, or field-based environments. - Strong understanding of learning principles, blended learning design, digital learning, and behavioural development. - Demonstrated ability to assess organisational capability needs and develop scalable learning solutions that deliver proven performance outcomes. - Worked at a senior level, shaping leadership interventions which have delivered proven leadership capability shifts. - Experience working to a governance framework, overseeing regulatory and mandatory compliance. - Comfortable operating in a fast-paced, commercially driven environment with multiple priorities. Experience of working with a clinical workforce is desirable. - Experience building sustainable learning ecosystems, including train-the-trainer models, communities of practice, and learning pathways. Benefits - Wellbeing Support: 24/7 Employee Assistance Programme and GP service plus an in-house Mental Health First Aider programme. - Additional Reward: bonus scheme based on business performance. - Extra Leave: Birthday off and option to buy 3 more days. - Family Support: Enhanced maternity/paternity leave. - Financial Security: Life assurance and pension scheme.