Senior Data Scientist ( Deep Learning, NLP, LLM & Gen AI) Full Time

Job Title: Senior Data Scientist ( Deep Learning, NLP, LLM & Gen AI)

Department: Artificial Intelligence

Summary:

We are seeking a highly skilled and experienced Data Scientist with a 8-12 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role.

• The ideal candidate should possess in-depth knowledge of Lang Chain and Open LLM frameworks and be proficient in creating cutting-edge NLP models and Generative Adversarial Networks (GANs), Autoencoders, transformers, BERT Word/Doc to Vector, as well as computer vision models using GANs, Autoencoders, and Variational Auto encoders (VAE). The candidate should also be an expert in Python code refactoring and have hands-on experience in developing end-to-end NLP Deep models. It is expected that the candidate has created at least one GANs model from scratch and has a track record of optimizing Deep models.
• The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role.

Primary Skills:

Data Science, ML, Deep Learning, NLP, LLM, Gen AI, Chat Bot, Azure ML, ML Ops, LLM Ops, Python, SQL, Statistics, Probability, Mathematics, Differential Calculus,

Secondary Skills:

AWS ML, GCP ML, System Optimization, Data Bases, Cloud, Scaling ML/AI Models

Responsibilities:

• Contribute to the design and implementation of state-of-the-art AI solutions.
• Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI.
• Collaborate with stakeholders to identify business opportunities and define AI project goals.
• Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges.
• Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases.
• Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities.
• Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment.
• Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems.
• Utilize optimization tools and techniques, including MIP (Mixed Integer Programming).
• Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models.
• Implement CI/CD pipelines for streamlined model deployment and scaling processes.
• Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines.

Qualifications:

• Bachelor’s or master’s degree in computer science, Engineering, or a related field.
• Azure machine learning/Azure AI certification preferred
• Minimum 8 years of experience in Data Science, Machine Learning, Deep Learning and NLP.
• Minimum 6 years experience in NLP and NLP Applications
• Minimum 2 year experience in LLM and Generative AI
• Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions.
• Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels.

Preferred Skills and Experience:

• Strong experience in designing, building, and deploying scalable machine learning models in cloud platforms such as Azure or AWS
• Experience with a variety of generative AI models and techniques.
• Experience with deep learning models such as GANs, diffusion models, and transformers.
• Experience with prompt engineering and machine learning optimization
• Experience with computer vision and natural language processing.
• Experience with reinforcement learning.
• Experience with distributed computing and scalable systems.
• Experience with DevOps and CI/CD.
• Experience with machine learning ethics
• Experience with generative AI applications in specific domains such as talent management, finance, or manufacturing
• Excellent communication and interpersonal skills.