Machine Learning Engineer - Deep Learning & Python (MSc / PhD)

Location : Global - Fully Remote

Employment Type : Contract / Freelance

Total Experience : 5 - 21 years

Key Responsibilities :

- Develop, implement, and validate machine learning and deep learning models.

- Design, build, and optimize machine learning training and inference pipelines.

- Implement model components, algorithms, data pipelines, and evaluation systems.

- Develop reproducible machine learning workflows using Python and command-line tools.

- Work on numerical computing, computational methods, and engineering optimization.

- Optimize model performance, memory utilization, computational efficiency, and inference throughput.

- Debug complex programming, numerical, and system-level issues.

- Implement and modify machine learning solutions to meet specific technical requirements.

- Review, test, and validate machine learning implementations for correctness and performance.

- Create, solve, assess, and review challenging machine learning engineering tasks.

- Effectively incorporate coding agents and AI-assisted development tools into the Python development workflow.

- Maintain clear technical documentation and ensure the quality and reliability of completed deliverables.

Required Qualifications :

- Master's degree (MSc) or PhD.

- Strong professional, research, or academic experience in Machine Learning.

- Advanced practical proficiency in Python programming.

- Hands-on experience with machine learning and deep learning model development.

- Practical understanding of model training, inference, and evaluation workflows.

- Experience using coding agents or AI-assisted coding tools as part of the development workflow.

- Ability to solve complex technical, mathematical, and computational problems.

- Experience developing reproducible Python-based engineering workflows.

- Strong analytical, problem-solving, and technical communication skills.

Preferred Qualifications :

- Experience working at an established technology company, AI laboratory, research organization, or recognized engineering environment.

- Strong academic or research background in Machine Learning, Deep Learning, or Artificial Intelligence.

- Experience developing and optimizing machine learning models and large-scale computational systems.

- Familiarity with numerical methods, performance benchmarking, and inference optimization.

- Experience with model evaluation, debugging, and computational efficiency improvements.

- Contributions to recognized open-source projects or impactful academic research.

- Ability to independently solve challenging machine learning implementation and engineering problems.