AI Machine Learning Engineer

Cayuse Holdings•Cedar Park, TX

2d•Hybrid

About The Position

The AI/ML Engineer enhances data collection procedures to include information that is relevant for building analytics and machine learning systems. Processing, cleansing, and verifying the integrity of data used for analysis. Doing ad-hoc analysis and presenting results in a clear manner. Focused on generating, maintaining and delivering detailed and accurate reporting on the information gathered and reported by artificial intelligence systems, with the goal of maximizing ROI from the rush of new data generated. This position performs all duties and responsibilities in accordance with the Mission, Vision, and Core Values of Cayuse.

Requirements

1-3 years of experience in the field or in a related area. Has knowledge of commonly used concepts, practices, and procedures within a particular field. Relies on instructions and pre-established guidelines to perform the functions of the job. Primary job functions do not typically require exercising independent judgment.
4-7 years of experience in the field or in a related area. Familiar with standard concepts, practices, and procedures within a particular field. Relies on limited experience and judgment to plan and accomplish goals. A certain degree of creativity and latitude is required. Works under limited supervision with considerable latitude for the use of initiative and independent judgment.
8 or more years of experience, relies on experience and judgment to plan and accomplish goals, independently performs a variety of complicated tasks; may lead and direct the work of others. A wide degree of creativity and latitude is expected.
Strong knowledge of programming languages (e.g., Java, Python, C#), software design patterns, and system architectures (e.g., microservices, service-oriented architecture).
Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their architectural principles.
Excellent analytical and problem-solving skills to address complex technical challenges.
Strong verbal and written communication skills to effectively collaborate with team members and stakeholders.
Must be able to pass a background check. May require additional background checks as required by projects and/or clients at any time during employment.
Proficiency in programming languages (e.g., Python, SQL).
Proficiency in open-source machine learning (ML) and artificial intelligence (AI) frameworks (e.g., TensorFlow, PyTorch, Scikit-Learn).
Exceptional understanding of data processing services
Exceptional understanding of feature engineering and model tuning processes.
Exceptional problem-solving skills using algorithm optimization.
Excellent data analysis skills
Exceptional interpersonal skills with the ability to communicate in a clear, professional, and articulate manner.
Exceptional verbal and written communication skills.
Excellent organizational, analytical, and problem-solving skills with high-level attention to detail.
Strong multitasking skills with the ability to manage multiple design streams across concurrent work effort.
Must be self-motivated and able to work well independently as well as on a multi-functional team.

Nice To Haves

Bachelor’s or master’s degree in Computer Science, Machine Learning, or related field.
Proven experience as an AI/ML Engineer or similar role.
Strong understanding of machine learning algorithms and principles.
Familiarity with deep learning frameworks such as TensorFlow or PyTorch.
Proficiency in programming languages like Python, R, or Java.
Experience with data preprocessing and feature engineering.
Strong analytical and problem-solving skills.

Responsibilities

Develop, test, and optimize machine learning models for classification, regression, clustering, or recommendation tasks.
Collaborate with cross-functional teams to integrate AI solutions into existing systems to align with business needs.
Stay updated on the latest advancements in AI technologies and methodologies.
Deploy trained models into production environments using APIs, containers (e.g., Docker), or cloud services (AWS, GCP, or Azure).
Monitor model performance, detect drift, and implement improvements or retraining strategies to ensure models remain accurate over time. Fine-tune models for performance and efficiency.
Troubleshoot and resolve issues related to AI models and implementations.
Document and share improvements and experiences in product troubleshooting and technical solutions.
Develop automated pipelines for continuous integration, delivery, and model retraining (CI/CD).
Ensure AI models comply with industry regulations, address biases, and adhere to ethical standards.
Other duties as assigned.