Artificial Intelligence Engineer

NOTE: To apply for this position, you should have a working project based on the skills mentioned below. You would need to submit screenshots of the running application. This is the only selection criteria.

Company Description

AINE AI is a deep tech company that specializes in developing AI-enabled technology products. Our APIs and customizable hosted products allow legacy and developing software to integrate AI modules readily available in the market.

Key Responsibilities:

* Model Development: Design, build, train, and fine-tune machine learning models to solve specific business problems.

* AWS Integration: Leverage various AWS services for the AI/ML lifecycle, including Amazon SageMaker, S3 for data storage, EC2 for compute, and Lambda for serverless functions.

* Data Handling: Collaborate with data scientists and data engineers to manage and optimize data pipelines, ensuring data quality and availability for model training.

* Deployment and MLOps: Deploy models into production, monitor their performance, ensure accuracy, and maintain the systems in an MLOps (Machine Learning Operations) environment.

* Collaboration: Work within cross-functional teams (software engineers, data scientists, product managers) to align AI solutions with business objectives.

* Optimization & Scaling: Focus on optimizing model performance, ensuring scalability, reliability, and cost-effectiveness of AI solutions on the AWS cloud.

* Code Review & Best Practices: Participate in design discussions, conduct code reviews, and champion best practices for software development and AI/ML systems.

Required Skills and Qualifications:

* Education: A Bachelor's degree in Computer Science, Data Science, Engineering, or a related quantitative field.

* Experience: 2+ years of professional, non-internship experience in an AI Specialist, Data Scientist, or Machine Learning Engineer role.

* Programming Languages: Strong proficiency in Python is essential, and experience with other languages like Java or R may be beneficial.

* ML Frameworks: Hands-on experience with AI frameworks and libraries such as TensorFlow, PyTorch, or Scikit-learn.

* AWS Services: Solid experience with core AWS services and specific AI/ML tools (e.g., S3, EC2, Lambda, and especially Amazon SageMaker).

* Problem-Solving: Strong analytical and problem-solving skills, with the ability to work with complex datasets.