AI Engineer (hybrid/onsite first 90 days)

Description

Job Description

The AI Engineer is an expert in designing, developing, and deploying artificial intelligence solutions that enhance business performance and customer experience. This role will own key components of the company’s AI infrastructure, from data pipelines to model deployment, while collaborating across departments to identify automation and optimization opportunities. The AI Engineer acts as a bridge between data science, engineering, and product teams, turning complex machine learning concepts into practical, scalable applications that support business objectives.

This role requires deep technical expertise, strong problem-solving skills, and the ability to communicate complex technical concepts clearly to non-technical stakeholders.

Requirements

Job Duties

• Build, train, and deploy machine learning models for production use across various business applications.
• Develop and maintain data processing pipelines that ensure high-quality, reliable input for AI systems.
• Collaborate with developers, analysts, and business leaders to identify AI-driven opportunities for innovation and efficiency.
• Optimize and monitor AI systems for accuracy, scalability, and performance.
• Participate actively in code reviews, deployment processes, and documentation of AI models and systems.
• Uphold best practices in data ethics, security, and model transparency.
• Stay current with emerging technologies and techniques in machine learning, large language models (LLMs), computer vision, and AI infrastructure.
• Mentor junior team members and provide technical leadership in AI development practices.
• Communicate project updates, findings, and insights effectively across the organization.
• Support management in evaluating AI vendors, tools, and frameworks for future initiatives.

Knowledge, Skills, and Abilities

• Strong understanding of training AI models.
• Strong programming skills in Python or similar, and experience with frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar frameworks.
• Solid understanding of machine learning theory, model evaluation, and algorithmic optimization.
• Working knowledge of cloud services (AWS, Azure, or GCP) for deploying AI models at scale.
• Strong problem-solving, analytical, and decision-making skills.
• Clear verbal and written communication skills.
• Ability to work independently and collaboratively in a team environment.
• Attention to detail, creativity, and customer focus.

Minimum Requirements

Education

• Bachelor’s Degree in Computer Science, Data Science, Engineering, or related field required.
• Master’s Degree or equivalent experience in AI/ML fields preferred.

Experience

• 1-3 years of experience in applied machine learning or AI engineering.
• Proven experience deploying ML models or AI-based systems in production.
• Familiarity with version control (Git), Docker, and CI/CD practices.
• Previous experience with data pipelines and tools such as Airflow, Spark, or similar frameworks.
• Previous experience building APIs and integrating AI models into production systems.

Position Type/Expected Hours of Work

This is a full-time position, Monday through Friday.

Expectations

• Open and honest communication with leadership and peers.
• Own your plan, own your work.
• Always follow up and follow through.
• Stay positive, own your mood.

Physical Demands
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job.

Other Duties
Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities and activities may change at any time with or without notice.

SD Wheel is an Equal Opportunity Employer and does not make employment decisions on the basis of race, color, religion, sex (including pregnancy and gender identity), national origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other characteristics protected by law.