Job Description

Choice Talents NG is a leading talent acquisition and human resources consulting firm dedicated to helping organizations identify, attract, and retain top talent across various industries. With a focus on excellence, integrity, and innovation, we provide customized recruitment solutions, talent management services, and workforce development programs to help our clients achieve their business objectives and drive growth. Our team of experienced recruiters, HR professionals, and industry experts is committed to delivering exceptional service, building lasting partnerships, and empowering organizations to build high-performing teams. Join us in our mission to connect talent with opportunity and create value for both employers and candidates.

Position Overview:

We are currently seeking a highly skilled and motivated AI Engineer to join our team at Choice Talents NG. As an AI Engineer, you will play a key role in developing and implementing artificial intelligence (AI) solutions, machine learning algorithms, and data-driven applications to enhance our recruitment processes, talent management strategies, and HR analytics capabilities. You will collaborate with cross-functional teams, leverage advanced technologies, and apply data science principles to solve complex business challenges and deliver innovative solutions that drive business outcomes. Your expertise in AI, machine learning, and data engineering will contribute to our success in identifying, assessing, and matching top talent with our clients' needs.

Key Responsibilities:

1. AI Solution Development: Design, develop, and deploy AI-powered solutions and applications to automate and optimize recruitment processes, candidate sourcing, screening, and selection. Utilize machine learning algorithms, natural language processing (NLP), and predictive analytics to improve talent acquisition efficiency and effectiveness.

2. Data Modeling and Analysis: Collect, clean, preprocess, and analyze large datasets to extract actionable insights, patterns, and trends related to candidate profiles, job requirements, and hiring outcomes. Build predictive models, recommendation systems, and candidate scoring algorithms to enhance decision-making and talent matching.

3. Algorithm Development: Develop and implement machine learning algorithms, deep learning models, and statistical techniques to solve specific business problems, such as resume parsing, candidate ranking, skills assessment, and predictive modeling. Fine-tune models, optimize parameters, and evaluate performance metrics to achieve desired outcomes.

4. Software Development: Collaborate with software engineers, data engineers, and product managers to integrate AI solutions into existing systems, applications, and workflows. Develop APIs, microservices, and web interfaces to enable seamless interaction and integration with HR systems, databases, and platforms.

5. Model Deployment and Monitoring: Deploy trained models into production environments, cloud platforms, or edge devices, and monitor their performance, accuracy, and reliability. Implement monitoring, logging, and alerting mechanisms to track model performance, detect anomalies, and ensure continuous improvement and optimization.

6. Research and Innovation: Stay abreast of the latest developments, trends, and advancements in AI, machine learning, and data science fields. Conduct research, experiment with new techniques, and explore innovative approaches to address evolving business needs, improve processes, and deliver value-added services.

7. Collaboration and Knowledge Sharing: Collaborate with cross-functional teams, including recruiters, HR professionals, data scientists, and business stakeholders, to understand requirements, gather feedback, and deliver AI solutions that meet business objectives. Share knowledge, best practices, and lessons learned through documentation, presentations, and training sessions.

8. Ethical and Regulatory Compliance: Ensure compliance with ethical guidelines, data privacy regulations, and industry standards in AI development, data handling, and model deployment. Uphold ethical principles, transparency, and accountability in AI decision-making and algorithmic fairness.

Qualifications:

• Bachelor's degree or higher in Computer Science, Data Science, Artificial Intelligence, or related field.
• Minimum of 3 years of experience in AI engineering, machine learning, data analytics, or related roles.
• Strong programming skills in Python, Java, or other programming languages used in AI development.
• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and libraries.
• Knowledge of data engineering concepts, tools, and techniques for data preprocessing, feature engineering, and model training.
• Familiarity with cloud computing platforms (e.g., AWS, Azure, Google Cloud) and containerization technologies (e.g., Docker, Kubernetes).
• Excellent analytical, problem-solving, and critical thinking skills.
• Effective communication, collaboration, and teamwork abilities.