Job Description

As Sr. Engineer Consultant - AI Science you will design, develop and optimize Artificial Intelligence, SLM/LLM solutions to diverse real-world problems and implement cutting-edge generative artificial intelligence models and systems. This role includes a combination of implementing new algorithms, SLM/LLMs, performance/accuracy tuning and analysis, defining APIs, and analyzing functionality coverage to build larger, coherent toolsets and libraries. The ability to work in a multifaceted, product-centric environment with excellent interpersonal skills. 

• Leading the design, development, and implementation of end-to-end NLP/SLM/LLM solutions using Python, Pyspark, distributed computing framework and cloud platform.
• Driving Cognitive AI use cases with cross-functional teams delivering business value
• Data mining or extracting usable data from valuable data sources using SQL. 
• Ability to convert vision into strategy and create an execution plan
• Contributing to the research and development of novel generative models, exploring new algorithms and methodologies.
• Developing end to end analytical solutions, and articulating insight findings to leadership. Provide data-driven recommendations to business by clearly articulating complex modeling concepts through generation and delivery of presentations.
• Identifying and defining new process improvement and or business opportunities.
• Working in collaborative environment with global teams to drive AI solutioning of business problems
• Mentoring and guiding junior engineers, fostering a collaborative and innovative team environment.
• Working closely with management to prioritize business and information needs.

What we are looking for: -

You’ll need to have:

• Bachelor’s degree or four or more years of work experience.
• Four or more years of relevant work experience.
• Four or more years of experience in cognitive analytics and AI modeling. 
• Experience working in collaborative environment with global teams to drive AI solutioning of business problems and implement highly optimized AI algorithms.
• Experience in large-scale distributed systems capable of performing end-to-end AI training and SLM & LLM modeling includes orchestration, fine tuning, model serving in production environment (batch/real time).
• Ability to communicate complex model designs and outcomes in business terms to a non-technical audience.
• Knowledge of GPU/CPU architecture and distributed computing
• Working knowledge in advance Prompt engineering and optimizations techniques
• Exposure to large-scale AI training, understanding of the compute system concepts (latency/throughput bottlenecks, pipelining, multiprocessing etc) and related performance analysis and tuning
• Experience in Research and Development: Stay up-to-date with the latest advancements in generative AI, deep learning, and related fields. Contribute to the research and development of novel generative models, exploring new algorithms and methodologies.
• Understanding and ability to explain both the code and the underlying math used in algorithms/models. Proficiency in programming languages such as C/C++, Python, Java, debugging, performance analysis and relevant AI libraries/frameworks (TensorFlow, PyTorch, etc.)

Even better if you have :

• Advance degree in computer science, Mathematics, Data science or related field.
• Prior experience with Generative AI techniques applied to Large Language Models And multimodal learning (Image, Video, Speech etc.). Advance knowledge of mathematics, Statistics and algorithms. 
• Experience in GCP/Azure/AWS or any other cloud technology. Hands-on experience with inference and deployment environments would be an asset
• Experience in Research, prototype, and develop effective tools and infrastructure pipelines
• Publish innovative results on Github, scientific publications and patents. 
• Familiarity with telecommunications industry data and use cases.