Data, AI & Machine Learning

0 years

0 Lacs

Posted:1 day ago| Platform: Linkedin logo

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Job Type

Full Time

Job Description

Key Responsibilities


  • As a Senior Data Scientist specializing in Generative AI, you will:
  • Shape Next-Generation Solutions: Partner with cross-functional teams to design and implement AI-driven systems that transform user experiences and streamline business processes.
  • Enhance AI Through Data: Employ data-centric methodologies to improve model accuracy and responsiveness by curating high-quality datasets and optimizing real-time performance.
  • Finetune Industry-Specific Gen AI Models: Adapt and fine-tune large language models for domain-specific applications using advanced techniques like instruction tuning, domain adaptation, and reinforcement learning from human feedback (RLHF).
  • Develop Intelligent AI Agents: Architect and refine AI agents that solve complex business challenges, leveraging LLMs to deliver personalized, user-centric solutions.
  • Advance Generative AI Applications: Innovate with cutting-edge generative AI models such as LLM, VLM, GANs, and VAEs to create tailored applications for dynamic content creation, predictive analytics, and enhanced automation.
  • Scale AI with Cloud Technology: Deploy and scale LLM-based solutions on platforms like GCP, AWS and Azure to address real-world business problems with precision and efficiency.


Qualifications


Your Skills & Experience:


  • Bachelor s degree in computer science, data science, mathematics, or a related field.
  • At least two years experience as a machine learning engineer.
  • Advanced proficiency with Python, Java, and R code writing.
  • Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture.
  • In-depth knowledge of mathematics, statistics, and algorithms.
  • Superb analytical and problem-solving abilities. Set Yourself Apart With:
  • Experience in Docker, Kubernetes, Kubeflow, MLflow, DVC, Cloud platforms
  • ML Model deployments and serving
  • Model Monitoring, Management and Governance
  • ML Feature Store and Artefact Store
  • Orchestration and ML Pipelines Benefits of Working Here


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