CT_NITRO Experimental AI Engineer

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• The selected candidate — Leads the design, development, and deployment of advanced generative AI models, including large language models (LLMs), driving innovation and solving complex business challenges

• Oversees the end-to-end data science lifecycle, from data acquisition and preprocessing to model validation and optimization, ensuring best practices and high-quality outcomes

• Works on developing and deploying machine learning algorithms, ensuring models are optimized for performance and scalability

• Mentors and guides junior data scientists, fostering a collaborative environment and promoting knowledge sharing of cutting-edge techniques and tools

• Partners with cross-functional teams to integrate AI-driven insights into products and services, translating sophisticated models into practical, scalable solutions that drive measurable impact

• Implementing AI solutions that integrate seamlessly with existing business systems to enhance functionality and user interaction.

• Reviewing complex data sets to establish data quality and highlighting where data cleansing is required to remediate the data

• Designing and implementing data models to manage data within the organization,

• Migrating data from one system to another using multiple sources, identifying and implementing storage requirements

• Analyzing the latest trends such as cloud computing and distributed processing, and their uses in business, building industry knowledge

• Peer reviewing models and working with relevant business areas to seek their input and ensuring they are fit for the designed purpose

• Automating important infrastructure for the data science team.

• Staying current with AI trends and suggesting improvements to existing systems and workflows.

• 8+ years’ experience in machine learning, large scale data acquisition, transformation, and cleaning, both structured and unstructured data

• Experience with generative LLM fine-tuning and prompt engineering.

• Proficiency with data wrangling, visualization, and modeling in Python

• Experience in ML/NLP algorithms, including supervised and unsupervised learning.

• Good knowledge with cloud ecosystems, Azure is preferred

• Experience in machine learning frameworks and tools (e.g., sci-kit-learn, Keras, Tensor Flow, MXNet, PyTorch, MLlib)

• Strong programming skills in Python

• Experience with tools in the distributed computing, GPU, cloud platforms, and Big Data domains (e.g., GCP, AWS, MS Azure, Hadoop, Spark, Databricks) is a plus

• Experience with SQL, Document DBs and Vector DBs

• Batch Processing - Capability to design an efficient way of processing high volumes of data where a group of transactions is collected over a period Data

• Visualization and storytelling - Capability to assimilate and present data, as well as more advanced visualization techniques. Capability to engage and explain data creating a narrative around data visualization

• Knowledge of containerization platforms like Docker is a plus.

• Experience with Git and modern software development workflow.

• Non-Technical
  
  Skills:

• Strong team and business communication skills – can walk through and approach with technical clients or explain tricky concepts to non-technical people

• Must thrive in a fast-paced environment and be able to work independently.

• Excellent in communication skills

• Education

• Bachelor/Master/PG in Artificial Intelligence, Analytics, Data Science, Computer Science, Engineering, Information Technology, Social Sciences or related fields preferred

• Strong analytical skills and problem-solving ability

• A self-starter, independent-thinker, curious and creative person with ambition and passion

• Excellent inter-personal, communication, collaboration, and presentation skills

• Customer focused

• Excellent time management skills

• Positive and constructive minded

• Takes responsibility for continuous self-learning

• Takes the lead and makes decisions in critical times and…