Responsibilities:

• Utilizing Large Language Models (LLMs), open-source tools, machine learning, and numerical programming frameworks to build transformative solutions.
• Possess a strong understanding of AI models, LLMs, and AI-specialized infrastructure, particularly regarding current trends and issues affecting businesses.
• Experienced in working with open-source models (TensorFlow, PyTorch, Hugging Face Transformers), cloud solutions, internal systems, and external partners to deliver optimal AI solutions.
• Optimizing existing generative AI models to enhance performance, scalability, and efficiency.
• Developing and maintaining AI pipelines, including data preprocessing, feature extraction, model training, and evaluation.
• Ensuring best practices in AI problem-solving through thorough analysis, research, continuous experimentation, documentation, rapid prototyping, and extensive testing.

 

Requirements : 

• 6-8 years of hands-on experience in machine learning and deep learning. Strong understanding of Deep Learning algorithms in at least two AI domains (e.g., Computer Vision, NLP/NLG, Time Series Forecasting).
• Proficient in Python with extensive experience in machine learning frameworks like PyTorch, TensorFlow, and Keras.
• Adept at modelling problems into Deep Learning frameworks.
  Experience building, measuring, and iterating on neural network architectures.
  Experience working with data teams for data collection and organization.
• Results-oriented with experience in developing pipelines for ML/NLP model monitoring, extraction, indexing, building, and tuning.
• Skilled in defining validation strategies, pre-processing/feature engineering techniques, and data augmentation pipelines.
• Expertise in data exploration and visualization to understand data distributions and their impact on model performance.
• Experience with GPU/CUDA for accelerating deep learning model training. 


Secondary Skills:

• Machine Learning Model Testing and Validation:
• Conduct thorough testing and validation of AI models for reliability, scalability, and security.
• Technical Mentorship:
• Ability to provide technical guidance and mentorship to junior team members.
• Staying Up to Date with AI Advancements:
• Demonstrated interest in keeping up to date with the latest advancements in NLP, ML, and AI.