• Develop and maintain model training, validation and inference pipelines. • Design feature and data pipelines that support machine learning applications in production. • Convert models developed in exploratory environments into reproducible, scalable pipelines. • Integrate machine learning solutions into the organization’s data ecosystem. • Collaborate with engineering, DevOps and DataOps teams to evolve the platform and the organization’s machine learning practices. • Work closely with data scientists to operationalize analytical models. • Support the transition of models from exploratory environments to production pipelines. • Build pipelines that enable recurring training, updating and model evolution. • Ensure models can run at scale and meet performance requirements for operational use. • Prepare, structure and transform the data required for model training and execution. • Develop data pipelines and feature engineering focused on machine learning applications. • Work with data engineering to ensure the availability and quality of the data used by models. • Implement monitoring mechanisms for model performance, stability and behavior in production. • Support the identification of model degradation and the need for retraining. • Contribute to the continuous improvement of machine learning solutions in production. • Ensure software development best practices are applied to machine learning solutions. • Use code versioning, code review and engineering practices for developing ML pipelines. • Contribute to the standardization and evolution of the area’s machine learning engineering practices.

Role Description Tierra del Sol Foundation is seeking an enthusiastic and engaging E-Learning Instructor to develop and facilitate virtual classes for adults with developmental disabilities. Courses may include topics such as Art, Communication, Career Exploration, Fitness, Lifestyle, Personal Development, and other areas that promote lifelong learning and personal growth. The E-Learning Instructor is responsible for: - Creating lesson plans - Delivering interactive virtual instruction - Maintaining training records - Supporting participant engagement while upholding the organization's mission, vision, and values Essential Responsibilities: - Develop and facilitate engaging virtual courses through online learning platforms - Create and maintain lesson plans, training materials, and course content - Collaborate with the Learning & Development Program Manager to develop training schedules and course offerings - Track and submit attendance and participation records - Foster a positive and inclusive learning environment - Adapt teaching methods to meet diverse learning needs - Communicate participant or staff concerns to leadership as needed - Continuously improve training content and instructional methods - Perform other duties as assigned Qualifications - Experience teaching, training, facilitating, or presenting to groups - Strong communication, organizational, and interpersonal skills - Ability to engage diverse learners in a virtual environment - Proficiency with Google Workspace, Microsoft Office, Zoom, Google Meet, and other online platforms - Knowledge of person-centered practices preferred - Bilingual Spanish preferred - Current First Aid/CPR and Handle with Care (HWC) certifications preferred - Ability to pass a Live Scan background check, drug screening, TB test, and pre-employment physical Work Environment This position requires flexibility, strong time management, and the ability to work effectively in a fast-paced environment while managing multiple responsibilities. Company Description Tierra del Sol Foundation is an Equal Opportunity Employer.

• Develop and deploy ML and GenAI capabilities into production applications • Build and improve ML models and LLM-powered features (RAG, agents, or classification/NLP as needed) • Prepare training and evaluation datasets; implement reproducible experiments • Integrate models into applications via APIs, batch jobs, or real-time services • Implement monitoring for drift, latency, cost, and quality; iterate from feedback • Collaborate with product, data engineering, and security on responsible AI practices • Document architectures, prompts, evaluation metrics, and runbooks • Support CI/CD and containerized deployment of ML services

• Build, maintain, and improve production machine learning systems that support search, recommendations, personalization, computer vision, and predictive modeling. • Contribute to search and discovery improvements, including ranking, filtering, relevance, exact match, boolean logic, and LLM-powered enhancements. • Develop and integrate machine learning models that improve recommendation quality, search accuracy, behavioral analytics, and personalized user experiences. • Write clean, reliable, and maintainable code for ML pipelines, model development, experimentation, and production workflows. • Work with large-scale datasets to train, evaluate, monitor, and improve ML systems. • Collaborate with Data Science, Product, Engineering, and other cross-functional partners to understand requirements, evaluate tradeoffs, and deliver ML solutions that create measurable product and business impact. • Participate in technical design discussions for ML systems, including model architecture, data pipelines, evaluation methods, deployment approaches, monitoring, and scalability.