Get started on an exciting career at Element! Element employees make a difference in the lives of others every day. We are re‑defining the fleet management industry to be people first, then business – delivering on our promise of a superior client experience. About the RoleWe’re looking for a detail‑oriented, reliability‑focused, and methodical professional to join our team as an Applied AI Specialist – Data Systems. In this role, you will build and maintain production‑grade data foundations that directly enable machine learning model training, experimentation, and deployment. The position independently owns small AI‑ready datasets, feature pipelines, and data services that power AI‑enabled products, ensuring reliable, scalable, and well‑governed data for model development and inference in production environments. What You’ll DoDesign, build, and maintain data pipelines that support machine learning experimentation, model training, and production inference workloads. Prepare curated datasets for supervised and unsupervised learning use cases, including feature extraction, transformation, normalization, and labeling workflows. Partner with AI engineers to support algorithm development, feature engineering, and model performance optimization. Develop and operationalize data workflows supporting model deployment, monitoring, retraining, and version control. Implement data integration patterns for ML pipelines using tools such as MLflow, Airflow, dbt, and CI/CD workflows. Support scalable model serving environments and ensure data reliability for APIs and AI‑driven applications. Build, maintain, and optimize batch and/or streaming ETL/ELT pipelines using SQL and Python. Implement monitoring and alerting for model training datasets and inference inputs (freshness, drift, anomalies). Independently own small AI data components or features from design through production release. Contribute to code reviews, Git workflows, testing practices, and technical documentation. Basic QualificationsBachelor’s degree in Computer Science, Engineering, Data Science, or related field (or equivalent practical experience). 1–3 years of hands‑on experience (including internships/co‑ops) in data engineering, machine learning systems, or software engineering. Demonstrated experience supporting machine learning model experimentation, training pipelines, or deployment workflows. Strong proficiency in Python and SQL. Familiarity with ML frameworks such as scikit‑learn, TensorFlow, or PyTorch. Experience working with cloud platforms (AWS, Azure, or GCP). Preferred QualificationsFamiliarity with MLflow, Airflow, dbt, or similar orchestration/MLOps tools. Knowledge of vector databases (e.g., Pinecone, Weaviate, Bedrock Knowledgebase) and graph databases (Neo4j, Neptune). Experience with framework conversion (TensorFlow, PyTorch, TensorRT, ONNX) to inference optimization. Excellent communication, documentation, and collaboration skills. Location & CompensationToronto, Canada. The hiring base salary range for this position is $76,300–$104,900 annually. Actual compensation within this range will be dependent upon the individual’s knowledge, skills, experience, equity with other team members, and alignment with market data. Candidates hired to work in other locations will be subject to the pay range associated with that location. BenefitsA culture of innovation, empowerment, decision‑making, and accountability. Comprehensive health and welfare benefits that serve the needs of you and your family and foster a culture of wellness (for qualified roles). Paid time‑off programs (vacation, sick leave, and holidays) (for qualified roles). Background CheckApplicants will be required to undergo a background check only if and after a conditional offer of employment has been extended. Equal OpportunityElement Fleet Management and its wholly owned subsidiaries are an equal opportunity employer committed to diversity, equity, inclusion, and belonging. We are pleased to consider all qualified applicants for employment without regard to race, color, religion, genetic information, sex, gender identity, sexual orientation, age, marital status, family status, ancestry, national origin, citizenship, physical or mental disability, veteran status, military obligations or any other characteristic protected by federal, state and local laws. Disability‑related accommodations during the application and interview process are available upon request. If you require an accommodation with our hiring process, please send an email to or call (800) 665‑9744.#J-18808-Ljbffr