Senior AI Data Scientist: Lead Production ML & NLP

Requirements

• Proficiency in Python with a focus on AI libraries (e.g., TensorFlow, PyTorch, Keras),
• Strong understanding of machine learning algorithms and deep learning architectures (e.g., CNNs, RNNs, GANs, Transformers),
• Experience with natural language processing (NLP) techniques and frameworks (e.g., NLTK, SpaCy),
• Familiarity with data manipulation and analysis libraries (e.g., Pandas, NumPy),
• Knowledge of cloud platforms for AI deployment (e.g., AWS, GCP or Azure),
• Experience with version control systems (e.g., Git) for collaborative development,
• 5+ years of experience in AI, machine learning, or related fields,
• Proven experience in developing and deploying AI models in production environments,
• Strong foundation in statistics and data analysis as it relates to AI,
• Familiarity with Agile methodologies and product development cycles,
• (Desirable) Experience with reinforcement learning and advanced AI techniques,
• (Desirable) Familiarity with ethical AI practices and regulations,
• (Desirable) Understanding of business applications and implications of AI technologies,
• (Desirable) Experience related to LLMs, Bedrock etc

What the job involves

• We are looking for an AI Data Scientist to join our Engineering team,
• As a Senior AI Data Scientist, you will lead the development and implementation of advanced artificial intelligence solutions,
• You will utilize machine learning techniques and deep learning architectures to solve complex problems and create innovative models that drive business value,
• You will work collaboratively with cross-functional teams to translate business requirements into AI-driven applications and insights,
• Design, develop, and deploy AI models and algorithms to address specific business challenges,
• Conduct research and experimentation to advance the state-of-the-art xghoner in AI and machine learning,
• Collaborate with product managers, engineers, and domain experts to identify opportunities for AI integration,
• Perform data preprocessing, feature engineering, and model selection for optimal performance,
• Evaluate and optimize AI models using performance metrics and model validation techniques,
• Communicate findings and insights effectively to stakeholders through data storytelling and visualization,
• Mentor and guide junior team members in AI concepts, tools, and best practices,
• Stay current with advancements in AI technologies and methodologies

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