Ai Engineer

Summary

Join ShyftLabs, a leading data and AI company, as an experienced AI Engineer. You will implement and optimize AI-powered products and solutions, working with cross-functional teams to apply, fine-tune, and scale AI models. Responsibilities include integrating AI into production systems, ensuring seamless deployment, and optimizing performance. The role requires a Bachelor's degree in a related field, 2+ years of experience in AI/ML engineering, strong programming skills in Python, and proficiency in SQL. The position offers a competitive salary, strong healthcare insurance and benefits, and the ability to work fully remote within the United States, with a preference for those near Austin, Texas. ShyftLabs also provides extensive learning and development resources.

Requirements

• Hold a Bachelor’s degree in Computer Science, AI, Data Science, or a related field
• Have 2+ years of experience in AI/ML engineering, software development, or data-driven solutions
• Possess strong programming skills in Python and experience with AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn
• Be proficient in SQL
• Have experience integrating AI models into scalable production systems
• Possess strong software engineering skills, including experience with API development, microservices, and distributed systems
• Demonstrate an understanding of system design and architecture to support AI applications
• Possess excellent problem-solving skills and the ability to optimize AI-driven applications
• Possess strong communication skills to collaborate with cross-functional teams and stakeholders

Responsibilities

• Apply and optimize AI models to enhance ShyftLabs' data and AI products
• Integrate AI solutions into scalable production environments
• Fine-tune models for performance, reliability, and cost efficiency
• Collaborate with engineers and data scientists to ensure seamless AI deployment
• Leverage cloud and infrastructure tools to support AI-driven applications
• Stay up to date with AI advancements and best practices
• Document processes and implementations to improve scalability and knowledge sharing

Preferred Qualifications

Familiarity with cloud platforms such as AWS, GCP, or Azure and MLOps best practices

Benefits

• Competitive salary
• Strong healthcare insurance and benefits package
• Fully remote work anywhere within the United States (preference for Austin, Texas)
• Extensive learning and development resources