Job Summary:

As a Junior AI Engineer, you will play a key role in assisting the development, deployment, and maintenance of AI systems and solutions. In addition to the core responsibilities of a Junior AI Engineer, you will have additional functions including coordinating with team members, conducting statistical analysis, automating infrastructure, building AI models, and transforming machine learning models into APIs for seamless integration with other applications.

Responsibilities:

Coordinating with other team members:

• Collaborate with cross-functional teams, including senior AI engineers, data scientists, and software developers, to understand project requirements and contribute to the development of AI solutions.
• Actively participate in team meetings, provide input, and support the coordination efforts for effective project execution.

Conducting statistical analysis and interpreting the results:

• Assist in applying statistical techniques to analyze data, identify patterns, and derive insights that guide the development and improvement of AI models.
• Collaborate with senior AI engineers and data scientists to interpret and communicate statistical findings, supporting data-driven decision-making processes.

Automating important infrastructure:

• Identify critical infrastructure components for AI systems, such as data pipelines, model training environments, or deployment mechanisms.
• Collaborate with senior AI engineers and software developers to design and implement automated solutions that optimize and streamline infrastructure processes, ensuring scalability, reliability, and efficiency.

Building AI models:

• Assist in designing and developing AI models using machine learning algorithms, deep learning architectures, and statistical modeling techniques.
• Contribute to the implementation and training of machine learning models using frameworks such as TensorFlow or PyTorch. Collaborate with senior AI engineers to optimize models for accuracy, performance, and efficiency.

Transforming machine learning models into APIs:

• Support the transformation of trained machine learning models into application programming interfaces (APIs) to facilitate seamless integration with other software applications.
• Collaborate with senior AI engineers and software developers to design and implement APIs that ensure appropriate functionality, security, and ease of integration for external applications or services.

Collaborating with cross-functional teams:

• Work closely with senior AI engineers, data scientists, and software developers to ensure alignment with project goals, requirements, and timelines.
• Actively participate in team discussions, contribute ideas, and provide technical support to foster a collaborative and innovative work environment.

Documentation and reporting:

• Assist in documenting the AI development process, including infrastructure setup, model building, and API implementation, ensuring clear and comprehensive records.
• Contribute to the preparation of reports and documentation summarizing the results, insights, and progress of AI projects, and present findings to relevant stakeholders.

Qualifications:

• Bachelor’s degree in computer science, data science, or a related field.
• Relevant certifications or coursework in AI and machine learning are a plus.
• Strong programming skills in languages like Python, Java, or C++.
• Familiarity with frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Basic understanding of machine learning algorithms, statistical modeling, and deep learning architectures.
• Exposure to data preprocessing, feature engineering, and exploratory data analysis.
• Experience with SQL or NoSQL databases and data manipulation.
• Familiarity with version control systems and software development best practices.
• Strong problem-solving skills and ability to learn new concepts quickly.
• Excellent communication and teamwork skills.