Machine Learning Engineer (Full Time)

Key Responsibilities:

• Develop and deploy end-to-end machine learning models, from data collection and preprocessing to training, validation, and production deployment.
• Implement and optimize models using techniques such as Convolutional Neural Networks (CNNs), Named Entity Recognition (NER), and others as needed.
• Collaborate with cross-functional teams to understand project requirements and deliver machine learning solutions that meet business needs.
• Continuously evaluate and improve model performance through A/B testing, monitoring, and iterative development.
• Maintain and update machine learning pipelines, ensuring seamless integration with existing systems.
• Contribute to the development of intuitive graphical user interfaces (GUIs) to facilitate the interaction with machine learning models.
• Stay updated with the latest trends and advancements in machine learning and artificial intelligence, applying new techniques and tools where appropriate.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
• Proven experience in developing and deploying machine learning models, including experience with deep learning frameworks such as TensorFlow, PyTorch, or similar.
• Strong programming skills in Python and familiarity with libraries such as scikit-learn, NumPy, pandas, etc.
• Experience with natural language processing (NLP) techniques, particularly with Named Entity Recognition (NER).
• Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and experience deploying models in cloud environments.
• Experience in building user-friendly GUIs and integrating machine learning models with front-end interfaces.
• Strong problem-solving skills and the ability to work independently and as part of a team.
• Excellent communication skills, with the ability to explain complex concepts to non-technical stakeholders.

Preferred Qualifications:

• Experience with large language models (LLMs) and their practical applications.
• Knowledge of data security and privacy considerations in handling sensitive data.
• Previous experience in a similar role within a mature, data-driven organization.

What We Offer:

• Competitive salary and benefits package.
• Opportunities for professional growth and career development.
• A collaborative and innovative work environment.
• Access to cutting-edge technologies and tools.