An Artificial Intelligence Engineer architects, fine-tunes, and deploys AI solutions to streamline operations and unearth insights, driving innovation across diverse industries. With expertise in machine learning and cognitive technologies, they build predictive models that not only solve current challenges but also anticipate future trends. Their work revolutionizes data utilization, enhancing decision-making and setting new standards for operational excellence.

*Job Duties and Responsibilities:

Development and Implementation (40%):

• Designing AI Models: Create and define the architecture of AI models suitable for specific tasks like image recognition, natural language processing, or predictive analytics.
• Coding and Programming: Write and debug code for AI applications using programming languages such as Python, Java, or R.
• Integration: Integrate AI models into existing systems, ensuring they work smoothly within the broader software infrastructure.
• Testing and Validation: Conduct rigorous testing to validate the accuracy and reliability of AI models. Implement automated tests and simulate various scenarios to check model performance.

Collaboration (20%):

• Team Meetings: Regularly meet with other engineers, data scientists, and project managers to coordinate on project progress and roadblocks.
• Stakeholder Engagement: Discuss and demonstrate AI solutions to non-technical stakeholders, explaining the benefits and limitations.
• Cross-Disciplinary Teams: Work across different areas of expertise, incorporating insights from data science, software engineering, and business analysis to enrich AI solutions.

Research and Innovation (15%):

• Literature Review: Stay updated with the latest research by reading scientific papers and attending conferences or webinars.
• Experimentation: Experiment with new algorithms, libraries, and technologies to find innovative solutions and improvements.
• Prototyping: Develop prototypes to explore new ideas quickly without the need for full-scale implementation.

Data Analysis and Modeling (15%):

• Data Collection: Gather and compile data from various sources necessary for training AI models.
• Data Cleaning: Preprocess data to improve its quality, including handling missing values, removing outliers, and standardizing formats.
• Feature Engineering: Extract and select relevant features from data that significantly improve model performance.

Performance Tuning & Diligence (10%):

• Model Optimization: Adjust and tune hyperparameters of AI models to enhance performance on specific metrics such as accuracy, speed, and efficiency.
• Resource Management: Manage computational resources to optimize the training and deployment of AI models, balancing performance and cost.
• Feedback Loop: Implement mechanisms to incorporate user feedback into model refinement and iterative development.
• Bias Detection: Analyze models for biases and implement strategies to mitigate any discriminatory effects in AI outputs.
• Privacy Protections: Ensure that data handling and AI processing comply with privacy regulations and ethical guidelines, implementing techniques like data anonymization
• Transparency: Work on making AI decisions more interpretable to users and stakeholders, which might involve developing or utilizing tools to explain AI model decisions

*Qualifications (Education, Experience, Certifications & KSA):

• Bachelor’s degree in computer science, Artificial Intelligence, Data Science, or a related field is required.
• Master's degree preferred.
• Relevant work experience may be considered as an equivalent for education requirements.
• 4+ years of professional experience in AI or related fields required.
• Experience in developing and implementing AI models and systems.
• Experience with cloud computing services (AWS, Azure, Google Cloud) is a plus.
• Portfolio of projects or contributions to open-source projects demonstrating expertise in AI.
• Proficient in programming languages such as Python, R, or Java. In-depth knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, NLTK).
• Strong ability to work with large data sets and complex algorithms. Proficient in data structures, statistical modeling, and computer science fundamentals.
• Excellent problem-solving skills and the ability to think algorithmically.
• Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Analytical and decision-making.
• Ability to work independently and as part of a team.
• Ability to meet deadlines and work under pressure.
• Ability to think strategically and tactically.

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The above statements are intended to describe the general nature and level of work being performed by people assigned to this job. They are not intended to be an exhaustive list of all responsibilities, skills, efforts or working conditions associated with a job.

We offer our employees a robust compensation package! Our comprehensive benefits include: medical, dental and vision insurance coverage; 100% company-paid life and disability coverage, 401k options with company match, three weeks PTO by the end of the first year and much more. Allied proudly promotes from within as part of a strong commitment to providing career growth opportunities for employees of all levels. Our diverse business portfolio allows employees broad career options with the advantage of staying with the same organization.

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