Artificial Intelligence (AI) Engineer

Description

Summary: An AI Engineer designs, builds, and deploys machine learning and AI solutions, focusing on data pipelines, model development, evaluation, optimization, and production deployment. Highlights: 1. Design, build, and deploy machine learning and AI solutions 2. Develop and validate models, ensuring accuracy, reliability, and maintainability 3. Collaborate across teams on requirements and responsible AI practices **Artificial Intelligence (AI) Engineer — Job Description** **Overview** An AI Engineer designs, builds, and deploys machine learning and AI solutions. They work on data pipelines, model development, evaluation, optimization, and production deployment, ensuring systems are accurate, reliable, and maintainable. **Key Responsibilities** * Gather and prepare training/evaluation data (cleaning, labeling strategy, feature engineering). * Develop machine learning models (classical ML and/or deep learning) aligned to business goals. * Train, evaluate, and validate models using appropriate metrics and experiments. * Tune performance (accuracy, latency, cost) and improve robustness/generalization. * Build and maintain ML pipelines (data ingestion, training workflows, model registry, CI/CD for ML if applicable). * Implement inference services/APIs and integrate models into applications. * Conduct error analysis and iterate on model improvements. * Ensure model monitoring in production (drift, performance, failure modes) and support retraining. * Collaborate with product, software engineering, and data teams on requirements and deployment. * Ensure responsible AI practices where applicable (safety checks, bias evaluation, auditability). **Required Qualifications** * Strong programming skills (Python is common) and experience with ML frameworks (e.g., PyTorch, TensorFlow, scikit\-learn). * Solid understanding of machine learning fundamentals (training/evaluation, overfitting, validation, regularization). * Experience with data processing and tooling (SQL, pandas, data pipelines). * Ability to deploy models (containers, APIs, workflow tools). * Proficiency with model evaluation and experimentation (metrics, cross\-validation, A/B or offline testing approaches). * Strong debugging and problem\-solving skills. **Preferred Qualifications** * Experience with large\-scale or production ML systems (batch and/or real\-time inference). * Knowledge of MLOps tooling (model versioning, monitoring, automation workflows). * Experience with natural language processing or computer vision (if relevant). * Familiarity with cloud services (AWS/Azure/GCP) and managed ML platforms. * Experience with transformers/LLMs and prompt/model evaluation workflows (if relevant). * Publication/competition or strong portfolio of AI projects. Pay: RO1,164\.540 \- RO1,483\.550 per month Work Location: In person