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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI engineer - **Company:** AI Powered LLC - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $160,000.0 - $200,000.0 - **Contract:** Permanent contract - **Skills:** Adaptable Database Systems, Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Microsoft Azure, Big Data, Code Review, Continuous Integration, Data Transformation, Relational Databases, Distributed Computing Environment, Github, Monitoring of Systems, Python (Programming Language), Machine Learning, NumPy, Performance Tuning, Recommender Systems, Blockchain, Tensorflow, Standard Sql, Unstructured Data, Data Processing, Google Cloud, Feature Engineering, Pytorch, Retrieval-Augmented Generation, Delivery Pipeline, Large Language Models, Apache Spark, IT Architecture, Deep Learning, Model Validation, Backend, Agentic-AI, Pandas, AI Platforms, Scikit Learn, Low Latency, Transformer Architectures, Data Management, Machine Learning Operations, Software Version Control, Data Pipelines, Docker, Databricks - **Published:** October 16, 2026 - **Apply:** https://www.builtincolorado.com/auth/login?destination=/job/senior-ai-engineer-large-scale-data-modeling-machine-learning/11697659 ## About the Role * 5+ years of relevant experience in AI engineering, machine learning, data science, or a closely related field preferred. * Strong proficiency in Python and its data science ecosystem. * Hands-on experience with large-scale data modeling, data processing, and machine learning workflows. * Strong understanding of machine learning algorithms, statistical modeling, and predictive analytics. * Experience working with large, complex datasets and designing effective data representations and features. * Proficiency with libraries and frameworks such as NumPy, Pandas, Scikit-learn, PyTorch, or TensorFlow. * Experience building, evaluating, tuning, and deploying machine learning models. * Strong knowledge of SQL and relational databases, with experience handling large volumes of data. * Understanding of data quality, feature engineering, model evaluation, and performance optimization. * Experience integrating AI/ML models into backend applications through APIs or services. * Strong analytical thinking, problem-solving, and communication skills., * Experience with distributed data processing tools such as Apache Spark or Databricks. * Experience with cloud AI and data platforms such as AWS, Google Cloud, or Microsoft Azure. * Familiarity with data orchestration and pipeline tools such as Airflow or similar technologies. * Experience with MLOps, model monitoring, experiment tracking, and automated model deployment. * Knowledge of deep learning, transformer architectures, embeddings, and vector databases. * Experience with large language models, RAG pipelines, AI agents, or fine-tuning models. * Experience developing recommendation systems, search ranking, customer segmentation, or demand forecasting. * Familiarity with Docker, CI/CD, and production infrastructure for machine learning systems. * Experience applying AI and machine learning to e-commerce, customer behavior, product discovery, or personalization., The ideal candidate is a hands-on AI engineer who understands both the theory and practical implementation of machine learning. You should be comfortable working with large datasets, designing scalable data models, building reliable AI pipelines, and deploying models that solve real-world business challenges. You should also be able to evaluate whether an AI approach is appropriate for a problem, select the right tools and algorithms, and work effectively with backend and product teams to deliver production-ready solutions., Artificial Intelligence * Cloud * Computer Vision * Hardware * Internet of Things * Software The Senior People Partner will strategically support GTM and Sales leaders, aligning talent priorities with business outcomes. Responsibilities include diagnosing organizational needs, managing talent and compensation programs, improving retention, partnering with People teams and centers of excellence, reinforcing company culture, and influencing leadership through data-driven insights. The role requires strong communication, coaching, consulting, facilitation, analytical, and problem-solving skills, plus experience using AI to automate routine work. Top Skills: AI ## Description We are looking for a talented Senior AI Engineer to design, develop, and implement intelligent AI solutions powered by large-scale data modeling and machine learning. The ideal candidate will have strong experience working with large and complex datasets, developing predictive models, building AI-powered systems, and transforming data into actionable insights. We are looking for an engineer who can take AI projects from research and experimentation through production deployment, helping us build scalable, data-driven products and intelligent e-commerce experiences., * Design, develop, and deploy AI and machine learning models using large-scale datasets. * Build and optimize data models to process, analyze, and extract meaningful insights from complex data. * Develop machine learning pipelines for data collection, preprocessing, feature engineering, training, validation, and deployment. * Apply statistical modeling, predictive analytics, and advanced machine learning techniques to solve business problems. * Design AI solutions that can scale efficiently as data volumes and business requirements grow. * Develop recommendation systems, personalization engines, forecasting models, and intelligent automation solutions where appropriate. * Explore and implement generative AI, large language models (LLMs), and retrieval-augmented generation (RAG) when suitable for project requirements. * Work with structured and unstructured data from multiple sources. * Collaborate with backend developers, data engineers, and product teams to integrate AI models into production applications and APIs. * Monitor model performance, data quality, accuracy, drift, and reliability in production. * Optimize models for performance, scalability, cost efficiency, and low-latency inference. * Establish best practices for model evaluation, experimentation, reproducibility, and version control. * Research emerging AI technologies and recommend practical solutions that deliver measurable business value.