Senior Machine Learning Engineer

Company Description

Data Doers is a team of Data & AI experts dedicated to enabling AI Innovation and Advanced Analytics for Startups and SMEs. The company believes in the power of AI-powered data analytics to drive informed decisions, improve efficiency, drive customer insights, foster innovation, and boost revenue and competitiveness for businesses of all sizes.

Role Description

We are seeking a talented and driven Data Scientist/Machine Learning Engineer to join our dynamic team. In this role, you will be instrumental in developing and deploying cutting-edge Natural Language Processing (NLP) models to solve complex business problems. You will leverage your expertise in machine learning, deep learning, and NLP to design, implement, and optimize models for text classification, named entity recognition, information extraction, and other related tasks. You will collaborate closely with cross-functional teams, contribute to the entire machine-learning lifecycle, and ensure the scalability and reliability of our deployed solutions.

Required Qualifications:

• 5+ years of experience in data science or machine learning.
• PhD or Master’s degree in Computer Science, Statistics, Mathematics, or a related field.
• Proven experience in Natural Language Processing (NLP) and developing state-of-the-art (SOTA) models.
• Experience in advanced prompt engineering.
• Proficiency in Python and relevant libraries such as TensorFlow, PyTorch, and Hugging Face Transformers.
• Strong background in machine learning algorithms, data structures, and statistical methods.
• Familiarity with Azure/Google distributed computing.
• Strong knowledge of data preprocessing, data cleaning, and data augmentation techniques.
• Experience with model evaluation, validation techniques, and hyperparameter tuning.
• Strong problem-solving skills and a passion for continuous learning.

Incentives and Benefits:

• Competitive Pay: Recognizing your expertise.
• Career Growth: Work with industry leaders, continuous learning.
• Tech Advancement: Exposure to cutting-edge AI in the International Market.
• Hybrid Work: Flexible work environment.
• Impactful Projects: Contribute to real-world solutions.