Industry : IT
Sub Department : Software Development
Department : Information Technology
: Borivali East
: Mumbai
: India
: 30 - 60 p.a (INR Lacs)
: 5 - 8 Year
WFH
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LLM and SLM Implementation and Optimization:
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Design and develop scalable
solutions using Large Language Models and Small Language Models for specific
business use cases.
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Optimize LLM- and SLM-powered
applications to balance cost, quality of response, and latency.
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Fine-tune and adapt both LLMs and
SLMs to meet targeted business requirements.
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Generative AI Applications:
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Develop innovative applications
leveraging generative AI techniques, including natural language generation,
summarization, and content creation.
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Create tailored Small Language
Models to address domain-specific challenges efficiently.
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Solve challenges related to
ethical AI, bias mitigation, and explainability in generative AI solutions.
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Research and Development:
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Experiment with cutting-edge AI
technologies and frameworks to enhance the functionality and efficiency of LLMs
and SLMs.
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Stay updated on the latest
advancements in generative AI and their practical applications.
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Contribute to the development of
proprietary models and algorithms when necessary.
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Collaboration and Integration:
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Collaborate with product and
engineering teams to integrate LLM- and SLM-powered solutions into business
applications.
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Partner with stakeholders to
identify specific pain points and tailor AI solutions accordingly.
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Performance Monitoring and Continuous Improvement:
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Monitor and evaluate the
performance of AI solutions, identifying areas for improvement.
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Implement iterative development
cycles to refine and enhance the effectiveness of LLM and SLM applications.
28, 66
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5+ years of experience in AI,
machine learning, or natural language processing, with a strong focus on LLMs,
SLMs, and generative AI.
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Proven track record of deploying
and optimizing LLM-based and SLM-based applications in production environments.
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Technical Skills:
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Expertise in working with popular
LLMs (e.g., OpenAI GPT, Anthropic, LLaMA) and building SLMs for specific use
cases.
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Strong proficiency in Python and
ML frameworks like PyTorch or TensorFlow.
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Hands-on experience with
fine-tuning, prompt engineering, and deployment of LLMs and SLMs.
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Knowledge of MLOps practices and
tools for scalable AI deployments.
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Familiarity with APIs and cloud
platforms (AWS, Azure, GCP) for LLM and SLM integration.
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Problem-Solving Skills:
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Deep understanding of trade-offs
between cost, quality of response, and latency in AI-powered applications.
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Ability to troubleshoot and
resolve challenges related to scalability, efficiency, and performance in AI
systems.
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Soft Skills:
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Strong communication skills to
explain complex AI concepts to technical and non-technical stakeholders.
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Collaborative mindset with the
ability to work in cross-functional teams.
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Proactive and self-motivated with
a passion for pushing the limits of AI technologies.