Associate Director - NLP/Machine Learning

Key Responsibilities :

- Lead and mentor a team of NLP engineers and data scientists to deliver world-class NLP solutions.

- Study and refine data science prototypes to convert them into scalable production models.

- Design and develop NLP applications aligned with product and business goals.

- Select and curate appropriate annotated datasets for supervised learning methods.

- Implement effective text representation techniques (e.g., embeddings, transformers, n-grams) to convert natural language into features for ML pipelines.

- Research, evaluate, and implement the best algorithms and tools for NLP tasks such as sentiment analysis, named entity recognition, and text classification.

- Train, evaluate, and optimize machine learning models; perform statistical analyses to refine performance.

- Integrate NLP models into production systems and deploy them at scale.

- Extend or build on machine learning libraries to meet custom NLP requirements.

- Stay up to date with emerging trends in machine learning, deep learning, and generative AI, and guide the team in adopting cutting-edge techniques.

Technical Skills :

- NLP Frameworks & Libraries : Hugging Face Transformers, spaCy, NLTK, Gensim.

- Machine Learning/DL Frameworks : TensorFlow, PyTorch, Scikit-learn.

- Text Representation Techniques : Bag of Words, TF-IDF, Word2Vec, GloVe, BERT, Sentence Transformers.

- Algorithms & Models : Classification algorithms (SVM, Random Forest), sequence models (LSTMs, GRUs), attention-based and transformer architectures.

- Data Handling : Pandas, NumPy, and tools for statistical analysis.

- MLOps & Deployment : Git, Docker, Kubernetes, MLflow, REST APIs, CI/CD pipelines.

- Cloud Platforms : AWS, Azure, or GCP for scalable deployments.

- Big Data Tools (Preferred) : Apache Spark, Hadoop, or data lake architectures.

Education & Qualifications :

- Proven track record of leading NLP projects and deploying solutions in production environments.

- Relevant certifications in AI/ML or cloud technologies (e.g., AWS ML Specialty, TensorFlow Developer) are a plus.

Professional Attributes :

- Excellent communication and problem-solving abilities.

- Strategic thinker who can balance technical depth with business priorities.

- Passion for staying ahead in the rapidly evolving AI/NLP landscape.