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.

Role Description As a Vector Applied Machine Learning Intern, you will contribute to developing reusable software to apply and scale research breakthroughs in machine learning and AI. You will collaborate with some of the best and brightest AI developers and machine learning researchers and will work with leading industry sponsors and health stakeholders to apply AI. You will work closely with a technical lead on your software development projects for day-to-day direction. Start date: September 8, 2026 End date: December 18, 2026 Key Responsibilities - Work on AI software development projects following an agile methodology with teams that can include Vector AI software developers, professional staff, researchers, and industry sponsors; - Develop reference applications and model templates that apply AI research to real-world problems using public and private data sets, providing software for training, testing, operating, and updating models; - Develop open source software for applying AI research techniques to common problems; - Contribute to industry projects that apply AI research to shared problems, contributing engineering expertise, and assisting with operational issues; - Develop prototypes and proofs of concept; - Report and present on software development including status and results; - Other duties as assigned. Qualifications - You are a self-identified Black or Indigenous student or postdoctoral fellow (Indigenous ancestry or heritage – First Nations (status or non-status), Métis or Inuit) or a recent graduate. - You are in second year or higher, studying at a Canadian university or college, or a recent graduate within one semester of graduation. - Experience in machine learning and/or statistics. - Data engineering background working with messy real-world data is preferred. - Analytical skills to identify signals in data and feasibility of prediction. - Knowledge and experience of Python. - Experience with parameter and architecture tuning of deep learning algorithms is preferred. - Experience in leading open source deep learning software frameworks (e.g., PyTorch, Tensorflow, and CUDA). - Experience with or Interest in AI Systems development, large language models, recommender systems, or deep generative models is a plus. Nice to Have - Data science experience is considered an asset. - Software engineering background with experience in industry is considered an asset. - Experience working on systems level programming on SLURM is an asset. - You are creative and enjoy collaborating within a small entrepreneurial environment that is results-driven. - You are motivated by continuous learning and the opportunity to make a difference and a real contribution to the AI ecosystem. Compensation $25/hour. Position Status This posting is for an existing vacancy. Inclusion and Equal Opportunity Employment Vector believes AI powers possibility by advancing cutting-edge research and translating it into real-world impact through collaboration with research, industry, and government. Vector is committed to fostering a diverse and inclusive culture that reflects its values. The Vector Institute welcomes applications from all qualified candidates, including those who are Indigenous, 2SLGBTQIA+, racialized persons/visible minorities, women, and people with disabilities. If you require an accommodation at any stage of the recruitment or selection process, please contact hr@vectorinstitute.ai . The Vector Institute team will be happy to work with you to ensure your experience is as inclusive and accessible as possible. If you have any questions, please contact internships@vectorinstitute.ai . Please address applications (cover letter and resume) to Enoch To, Program Coordinator, Research Operations & Academic Partnerships, using the link provided. The deadline for submission is May 28, at 1:00PM ET. We thank all applicants for their interest in this exciting opportunity and will be in touch with those whose qualifications most closely match with our needs. Please note that all interviews are currently being held remotely.

• Define and lead the architecture for scalable Machine Learning and AI platforms. • Design end-to-end ML workflows using Databricks, including: Feature engineering, Model training, Experimentation, Deployment, Monitoring • Architect scalable data pipelines for AI/ML workloads using: Apache Spark, Python, SQL • Establish MLOps best practices including: CI/CD for ML, Model versioning, Model governance, Automated retraining, Model drifting, Observability and monitoring • Design secure and compliant AI architectures aligned with governance and privacy standards. • Partner with Data Engineering teams to optimize data models and feature stores. • Guide Data Scientists and ML Engineers on scalable production design patterns. • Evaluate and integrate modern AI capabilities, including (this will be a plus): LLMs, Vector databases, Retrieval augmented generation (RAG), AI agents • Drive cost optimization, scalability, and operational excellence across ML platforms. • Define reference architectures and best practices across multiple ML teams (not just owning a single project). • Support stakeholder engagement and translate business needs into scalable technical solutions.