Job Description
Artificial Intelligence (AI) Engineer
Company: Robert Half
Location: Knoxville, TN
Salary: $117.20K - $140.70K/yr (Estimated pay)
Job Type: Full-time
Posted: 21 hours ago
Job Description
Robert Half is hiring an experienced Artificial Intelligence (AI) Engineer to design and implement cutting-edge AI and machine learning solutions to enhance our SaaS platform. You will collaborate with cross-functional teams to optimize workflows, improve customer experiences, and drive innovation through intelligent features.
Responsibilities
- Develop and deploy robust machine learning models for predictive analytics, generative AI, and other advanced capabilities within a SaaS environment.
- Create scalable data pipelines for model training, testing, and monitoring, ensuring optimal performance and reliability.
- Collaborate with product, engineering, and data teams to identify and implement AI-driven solutions that address business challenges.
- Design and integrate AI functionalities, such as recommendations and classification systems, while maintaining efficiency and accuracy.
- Incorporate AI models into cloud-based systems using APIs, microservices, and containerized infrastructure.
- Assess and implement third-party AI tools and frameworks to enhance productivity and product capabilities.
- Ensure models align with privacy, security, and fairness standards, maintaining compliance across all implementations.
- Document workflows, track experiments, and maintain reproducibility for all AI-related processes.
- Keep up-to-date with advancements in AI technologies, machine learning techniques, and SaaS architecture trends.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.
- At least 3 years of experience deploying machine learning models in production environments.
- Proficiency in Python and familiarity with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
- Hands-on experience with cloud platforms such as AWS, Google Cloud, or Azure, and container tools like Docker or Kubernetes.
- Knowledge of large language models (LLMs), vector databases, and modern AI development tools.
- Understanding of microservice architectures and API-based integrations.
- Strong grasp of data structures, algorithms, and software engineering principles.
- Experience with model experimentation and monitoring frameworks.