AI Machine Learning

As an AI / ML Engineer, youll:

• Work with large datasets to extract insights and build predictive models.
• Develop and implement machine learning and non-ML algorithms tailored to business problems.
• Use statistical languages such as Python, R, etc., to manipulate data and draw insights.
• Apply techniques like clustering, decision trees, boosting, neural networks, and more.
• Build and fine-tune models for NLP, Computer Vision, Time Series Forecasting, etc.
• Utilize LLMs (Large Language Models), perform fine-tuning, and implement GenAI solutions including Retrieval-Augmented Generation (RAG).
• Collaborate with functional teams to integrate models and monitor outcomes.
• Assist in evaluating the accuracy of data sources and improving data gathering techniques.
• Use Git for code version control and collaborate effectively in a team environment.

What Were Looking For:

• Bachelors or Masters degree in Computer Science, Mathematics, Statistics, or related disciplines.
• Strong foundational knowledge in data structures, algorithms, and applied statistics.
• Hands-on experience or academic projects using Python, R, or similar languages.
• Familiarity with ML libraries: TensorFlow, PyTorch, Scikit-learn, SciPy, XGBoost, etc.
• Exposure to NLP and Computer Vision libraries: SpaCy, NLTK, OpenCV, etc.
• Understanding of cloud platforms: Google Cloud Platform (GCP), AWS, Azure, etc.
• Exposure to LLM fine-tuning and GenAI tools is a must.
• A passion for continuous learning and the ability to adapt to new technologies quickly.