AI Developer 1

Key Responsibilities

• Collaborate with stakeholders to identify business challenges and opportunities where AI can provide solutions.
• Design and develop AI models, algorithms, and applications based on identified requirements and use cases.
• Apply machine learning techniques to analyze and process large datasets to extract meaningful insights.
• Implement data pre-processing, feature engineering, and model training and evaluation pipelines.
• Conduct exploratory data analysis to gain a deep understanding of datasets and uncover patterns and trends.
• Optimize and fine-tune AI models to improve accuracy, performance, and scalability.
• Integrate AI models into existing systems and applications, ensuring seamless functionality and compatibility.
• Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to ensure successful project execution.
• Document and communicate project progress, results, and insights to stakeholders in a clear and concise manner.
• Stay up to date with the latest advancements in AI, machine learning, and related technologies, and apply them to enhance existing solutions.
• Take over additional reasonable tasks that align with their abilities, if required.

Requirements & Tech Stack

• Solid understanding of statistical analysis, data visualization, and exploratory data analysis.
• Strong problem-solving skills and ability to translate business requirements into technical solutions.
• Excellent communication and teamwork skills, with the ability to collaborate effectively with cross-functional teams.
• Ability to learn quickly and adapt to new technologies and methodologies.

Qualifications

• Bachelor’s degree in computer science, software engineering, data science, information systems, machine learning, or a related field, or equivalent experience required.
• Less than 2 years of experience in machine learning engineering, MLOps engineering, platform engineering, DevOps engineering, software engineering, or a related technical field required.
• Certification in cloud platforms, DevOps, machine learning, container orchestration, automation, or platform engineering preferred.
• Certification in cloud engineering, infrastructure automation, or machine learning operations preferred.