Job Description

Deep understanding of ML Algorithms and Deep Learning: Develop and apply a strong understanding of various machine learning algorithms, including supervised and unsupervised learning, as well as deep learning techniques such as neural networks, CNNs, RNNs, and transformers.

Data Preprocessing: Perform data preprocessing and feature engineering to ensure the quality, relevance, and suitability of data for modeling purposes.

NLP Expertise: Possess practical experience and expertise in Natural Language Processing (NLP) techniques and frameworks to work on NLP-related projects effectively.

Model Building: Design, develop, and implement machine learning and deep learning models and algorithms to analyze complex data sets, uncover patterns, and extract actionable insights.

Model Evaluation: Conduct thorough model evaluation, fine-tuning, and optimization to ensure the models' performance meets high standards of accuracy and efficiency.

Tools Proficiency: Utilize popular machine learning and deep learning libraries and frameworks such as TensorFlow, PyTorch, scikit-learn, and Keras to build, train, and deploy advanced machine learning models.

Integration: Integrate developed predictive models seamlessly into existing systems, ensuring smooth operations and compatibility with the company's infrastructure.

Innovation and Research: Stay up-to-date with the latest advancements in machine learning, deep learning, and data science, and proactively contribute innovative ideas to improve existing processes and systems.

Collaborative Team Player: Collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to solve complex problems and implement solutions.

Job Type: Full-time

Pay: ?13,000.00 - ?15,000.00 per month

Schedule:

• Day shift

Experience:

• total work: 1 year (Preferred)

Work Location: In person