Senior AI Strategist

Job Description:

We are seeking an experienced and innovative Lead Data Scientist to spearhead our AI and Machine Learning initiatives. This role is ideal for a professional who can drive innovation in Classical Machine Learning, Conversational AI, and Deep Learning Systems while providing technical leadership and strategic direction to a team of data scientists.

The Lead Data Scientist will be responsible for overseeing model development, optimizing AI-driven solutions, mentoring junior team members, and collaborating with key stakeholders to align AI strategies with business goals. The ideal candidate should possess deep expertise in NLP, Large Language Models (LLMs), Generative AI, and MLOps to lead the development of scalable AI-driven solutions.

Key Responsibilities:

• Define and drive the AI/ML strategy with alignment with business objectives.
• Lead the research, design, and development of cutting-edge machine learning and deep learning models, including LLMs, GANs, VAEs, Transformers, CNNs, and RNNs.
• Establish best practices for data pipelines, feature engineering, model deployment, and AI governance.
• Evaluate emerging AI/ML technologies and recommend their adoption where beneficial.
• Architect and implement Generative AI solutions with a focus on improving conversational AI experiences.
• Optimize LLMs (GPT, BERT, T5, etc.) for various business applications, including prompt engineering, fine-tuning, and model interpretability.
• Work on text generation, semantic search, intent recognition, and AI-driven recommendation systems.
• Oversee end-to-end model lifecycle, from data collection and preprocessing to model deployment and monitoring.
• Implement MLOps best practices to streamline model retraining, CI/CD for ML pipelines, and productionization.
• Optimize models using hyperparameter tuning techniques such as grid search, Bayesian optimization, and neural architecture search.
• Lead and mentor a team of data scientists and ML engineers.
• Conduct code reviews, design discussions, and knowledge-sharing sessions.
• Guide junior team members on best practices in data science, deep learning, and software engineering.
• Partner with engineering, product management, and business stakeholders to integrate AI solutions into production.

Qualifications & Experience:

• Minimum 5+ years of hands-on experience in machine learning, deep learning, NLP, and AI-driven applications.
• Machine Learning & AI: Proficiency in Classical ML (Regression, Decision Trees, Random Forests, SVMs, Gradient Boosting, etc.) and Deep Learning (CNNs, LSTMs, GANs, Transformers, etc.).
• LLM & NLP Expertise: Strong experience with GPT, BERT, T5, Hugging Face Transformers, NLTK, and SpaCy.
• Programming & Tools: Proficiency in Python, PyTorch, TensorFlow, NumPy, Pandas, Scikit-learn, and MLOps tools (MLflow, Kubernetes, Docker, AWS SageMaker, Azure ML, etc.).
• Big Data & Cloud: Experience working with large-scale datasets, cloud-based AI solutions (AWS, Azure, GCP), and distributed computing frameworks (Spark, Dask, Hadoop).
• Model Deployment: Strong understanding of APIs, CI/CD pipelines for ML models, containerization (Docker, Kubernetes), and model monitoring.

Soft Skills & Leadership:

• Strong leadership skills with the ability to mentor and develop junior data scientists.
• Exceptional problem-solving and critical-thinking abilities.
• Strong communication skills to effectively convey complex AI concepts to business stakeholders.
• Proactive ownership of projects, ensuring timely delivery and alignment with business needs.
• Ability to manage multiple projects and prioritize effectively in a fast-paced environment.