New

AI/GenAI Engineer (Information Technology)/ 655 days ago

Apply

Job Preference:

Qualification:

Job Description:

? LLM and SLM Implementation and Optimization:

? Design and develop scalable solutions using Large Language Models and Small Language Models for specific business use cases.

? Optimize LLM- and SLM-powered applications to balance cost, quality of response, and latency.

? Fine-tune and adapt both LLMs and SLMs to meet targeted business requirements.

? Generative AI Applications:

? Develop innovative applications leveraging generative AI techniques, including natural language generation, summarization, and content creation.

? Create tailored Small Language Models to address domain-specific challenges efficiently.

? Solve challenges related to ethical AI, bias mitigation, and explainability in generative AI solutions.

? Research and Development:

? Experiment with cutting-edge AI technologies and frameworks to enhance the functionality and efficiency of LLMs and SLMs.

? Stay updated on the latest advancements in generative AI and their practical applications.

? Contribute to the development of proprietary models and algorithms when necessary.

? Collaboration and Integration:

? Collaborate with product and engineering teams to integrate LLM- and SLM-powered solutions into business applications.

? Partner with stakeholders to identify specific pain points and tailor AI solutions accordingly.

? Performance Monitoring and Continuous Improvement:

? Monitor and evaluate the performance of AI solutions, identifying areas for improvement.

? Implement iterative development cycles to refine and enhance the effectiveness of LLM and SLM applications.

Skills:

? 5+ years of experience in AI, machine learning, or natural language processing, with a strong focus on LLMs, SLMs, and generative AI.

? Proven track record of deploying and optimizing LLM-based and SLM-based applications in production environments.

? Technical Skills:

? Expertise in working with popular LLMs (e.g., OpenAI GPT, Anthropic, LLaMA) and building SLMs for specific use cases.

? Strong proficiency in Python and ML frameworks like PyTorch or TensorFlow.

? Hands-on experience with fine-tuning, prompt engineering, and deployment of LLMs and SLMs.

? Knowledge of MLOps practices and tools for scalable AI deployments.

? Familiarity with APIs and cloud platforms (AWS, Azure, GCP) for LLM and SLM integration.

? Problem-Solving Skills:

? Deep understanding of trade-offs between cost, quality of response, and latency in AI-powered applications.

? Ability to troubleshoot and resolve challenges related to scalability, efficiency, and performance in AI systems.

? Soft Skills:

? Strong communication skills to explain complex AI concepts to technical and non-technical stakeholders.

? Collaborative mindset with the ability to work in cross-functional teams.

? Proactive and self-motivated with a passion for pushing the limits of AI technologies.