Ai Ml Engineer

Job Profile Summary:

The Machine Learning Engineer role is responsible for the development and implementation of reliable AI systems. This includes integrating AI/ML models into real workflows, as well as supporting deployment and maintenance.

The role also includes responsibility for following best practices with which to optimize and measure the performance of our models and algorithms against business goals.

in machine learning solutions to serve our organization. This includes ownership or oversight of projects from conception to deployment with appropriate AWS services, Docker, MLFlow, and other. 

Job Description:

MAIN TASKS & RESPONSIBILITIES:

The following is a non-exhaustive list of responsibilities and areas of ownership of an AI/ML Engineer

- Build, maintain, and improve Python services and pipelines for AI workloads.

- Follow solid engineering principles. Produce clean, well tested, and production-ready code.

- Own projects from implementation to deployment, ensuring stability and performance.

- Deploy AI models and algorithms using appropriate techniques and technologies, such as containerization using Docker and deployment to cloud infrastructure (AWS).

- Run experiments, evaluate results, and interpret performance metrics.

Success Indicators for a Machine Learning Engineer

- You deliver robust, maintainable Python code.

- AI models run reliably in production with clear performance metrics.

- You collaborate effectively with teammates and communicate issues early.

- You continuously refine workflows, tooling, and code quality.

REQUIREMENTS

Education

BSc in Computer Science, Mathematics or similar field; Masters degree is a plus

Experience

- Minimum 3+ years experience as a Machine Learning Engineer or similar role

Skills & Knowledge

- Strong Python programming skills (testing, packaging, debugging, performance-aware coding).

- Experience building production systems or pipelines.

- Comfortable with Docker and cloud environments (AWS).

- Ability to take ownership of tasks and manage projects end-to-end.

- Excellent communication and documentation skills.

- Knowledge of AI techniques and algorithms, including embeddings, LLMs as a judge, etc.