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    Cardinal Financial Company, LP is looking for a Applied Artificial Intelligence Engineer | Remote

    Who We Are:

    Cardinal Financial is a nationwide direct mortgage lender that focuses on creating solutions for our borrowers, partners, and employees—to provide the very best experience. We are genuine and hard-working individuals who are not scared to improve and intentionally push beyond what is considered “good enough.”…
    Looking to join a company that values its people, innovates and expands on its proprietary technology, and is growing at a ridiculous rate?! Apply below!

    Who We Need:

    The Applied Artificial Intelligence (AI) Engineer helps to guide our business into the future by designing, developing, and implementing AI solutions that solve real-world problems and drive business value. Expertise in designing and implementing cloud AI infrastructures, machine learning techniques, and software engineering will be instrumental in creating intelligent systems that optimize processes, deliver actionable insights, and enhance user experiences across various domains. The Applied Artificial Intelligence (AI) Engineer interfaces with various technology teams at both ideation and implementation stages, lending expertise and guidance.

    What You Will Do:

    • Solution design: Collaborate with stakeholders to understand business operations and identify opportunities for AI-driven solutions. Design and architect end-to-end AI systems, including data acquisition, preprocessing, feature engineering, model selection, and deployment.
    • AI algorithm development: Develop and refine AI algorithms and models tailored to specific use cases. Utilize machine learning and other AI techniques to address complex problems and extract meaningful insights from data.
    • Model training and evaluation: Build, train, and fine-tune AI models using appropriate algorithms and frameworks. Implement rigorous evaluation methodologies to assess model performance, including metrics such as accuracy, precision, recall, and F1 score.
    • Model deployment and integration: Deploy trained models into production environments, ensuring scalability, reliability, and performance. Integrate AI solutions with existing systems or applications, collaborating with cross-functional teams to ensure seamless integration and interoperability.
    • Performance optimization: Identify and address performance bottlenecks in AI systems. Optimize models and algorithms for efficiency, speed, and resource utilization.
    • Conduct experiments and A/B testing to continuously improve model accuracy and performance.
    • Data analysis and visualization: Perform exploratory data analysis, uncover patterns, and derive insights from structured and unstructured data. Develop visualizations and interactive dashboards to effectively communicate findings and facilitate decision-making.
    • Collaboration and knowledge sharing: Work closely with multidisciplinary teams, including data scientists, software engineers, and domain experts, to ensure successful implementation of AI solutions. Share knowledge, best practices, and emerging AI trends with colleagues to foster a culture of innovation and continuous learning.
    • Documentation and reporting: Document code, algorithms, models, and workflows to ensure reproducibility and maintainability. Prepare technical reports, presentations, and documentation to communicate project progress, outcomes, and recommendations to stakeholders.

    What You Need:

    • Bachelor's or Master's degree in Computer Science, Data Science, Applied Mathematics, or a related field; or equivalent experience.
    • Proven experience as an AI Engineer, Machine Learning Engineer, or similar role, with a minimum of 2 years of AI industry experience.
    • 5+ years of experience in data science, software engineering, or a related field.
    • 1-2 years of experience in working in Model development and deployment lifecycle using ML infrastructure and MLOps in the Cloud.
    • Strong problem-solving skills and the ability to apply AI techniques to real-world scenarios, identifying the most suitable approaches for different use cases.
    • In-depth knowledge of document understanding techniques, such as text extraction, classification, entity recognition, information retrieval, and semantic analysis.
    • Strong proficiency in programming languages such as Python, Java, or C++, and experience with AI libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
    • Solid understanding of machine learning algorithms, statistical modeling, and data mining techniques.
    • Experience with data preprocessing, feature engineering, and data wrangling techniques to handle real-world datasets.
    • Knowledge of cloud platforms (e.g., Google Cloud, AWS, Azure) and their AI services for scalable and distributed computing.
    • Proficiency in data analysis and visualization tools (e.g., Pandas, Matplotlib, Tableau) to extract insights and communicate results effectively.

    What We Offer:

    • Strength, Stability, and Vision
    • Great compensation package
    • Opportunity for career growth
    • A commitment to be a relevant market leader - we are aiming for the top!
    • Octane, our engineered proprietary technology that is transforming the mortgage industry
    • An empowered culture where your ideas are important and your voice matters
    • Full Benefits, beginning the first day of the month following your start date, including – Medical, Dental, Vision, Life, Disability Insurance, and much more
    • Generous paid time off package that also includes all major holidays
    • 401K w/ 50% match - Beginning the 1st of the month following 30 days of employment

    Cardinal Financial is an Equal Opportunity Employer. We respect and aim to empower individuals and support the diverse cultures, perspectives, skills and experiences within our workforce. California residents click here to review Cardinal's California Employee Privacy Policy & Notice at Collection. The expected base salary for this position ranges from one hundred forty thousand dollars to two hundred thousand dollars, determined based on the applicant's experience, skillset, education, training, certificates, and licenses