Artificial Intelligence/Machine Learning Engineer - Python/NLP

Key Responsibilities :

- Design, develop, train, and deploy advanced AI/ML models and algorithms.

- Focus on building and implementing solutions utilizing Generative AI (Gen AI) techniques and frameworks.

- Develop and apply Natural Language Processing (NLP) models for various text-based applications (e.g., text generation, summarization, understanding, sentiment analysis).

- Work with large and complex datasets, performing data cleaning, preprocessing, feature engineering, and validation to prepare data for model training.

- Write high-quality, efficient, and scalable code primarily in Python.

- Utilize relevant AI/ML libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers).

- Integrate AI/ML models into existing applications and systems.

- Participate in the deployment, monitoring, and maintenance of AI/ML solutions in production environments.

- Stay updated with the latest advancements in AI, Machine Learning, Generative AI, and NLP research.

- Experiment with new technologies and methodologies to continuously improve model performance and capabilities.

- Collaborate effectively with cross-functional teams, including product managers, data scientists, software engineers, and domain experts.

- Communicate complex technical concepts and findings clearly to both technical and non-technical stakeholders.

- Apply strong analytical and problem-solving skills to address challenging AI/ML tasks and optimize model performance.

Required Skills & Qualifications :

- 2 to 15 years of professional experience as an AI/ML Engineer or in a similar role.

- Strong hands-on experience in AI/ML model development.

- Mandatory expertise in Python programming language for data science and machine learning.

- Mandatory experience with Natural Language Processing (NLP).

- Demonstrated experience or strong interest in Generative AI (Gen AI) techniques and models (e.g., LLMs, GANs, VAEs, Transformers).

- Solid understanding of machine learning fundamentals, algorithms, and statistical modeling.

- Experience with relevant AI/ML libraries and frameworks (e.g., TensorFlow, PyTorch, Keras, scikit-learn).

- Familiarity with data manipulation and analysis libraries (e.g., Pandas, NumPy).

- Excellent problem-solving, analytical, and debugging skills.

- Strong communication and collaboration abilities.

- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related quantitative field.

Preferred (Bonus) Skills :

- Experience with cloud platforms for AI/ML (e.g., AWS Sagemaker, Azure ML, Google Cloud AI Platform).

- Familiarity with MLOps practices, including model versioning, monitoring, and deployment pipelines.

- Experience with big data technologies (e.g., Spark, Hadoop).

- Knowledge of specific domain applications of AI/ML.

- Contributions to open-source projects or relevant publications.