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1 Day ago

Data Scientist - Artificial Intelligence/Machine Learning

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Indore, Madhya Pradesh, India
Information Technology
Full-Time
TechnoComp Computer Services Pvt. Ltd.

Overview

Description

JOB RESPONSIBILITY :

  • Collaborate with cross-functional teams, including data scientists and product managers, to acquire, process, and manage data for AI/ML model integration and optimization.
  • Design and implement robust, scalable, and enterprise-grade data pipelines to support state-of-the-art AI/ML models.
  • Debug, optimize, and enhance machine learning models, ensuring quality assurance and performance improvements.
  • Operate container orchestration platforms like Kubernetes, with advanced configurations and service mesh implementations, for scalable ML workload deployments.
  • Design and build scalable LLM inference architectures, employing GPU memory optimization techniques and model quantization for efficient deployment.
  • Engage in advanced prompt engineering and fine-tuning of large language models (LLMs), focusing on semantic retrieval and chatbot development.
  • Document model architectures, hyperparameter optimization experiments, and validation results using version control and experiment tracking tools like MLflow or DVC.
  • Research and implement cutting-edge LLM optimization techniques, such as quantization and knowledge distillation, ensuring efficient model performance and reduced computational costs.
  • Collaborate closely with stakeholders to develop innovative and effective natural language processing solutions, specializing in text classification, sentiment analysis, and topic modeling.
  • Stay up-to-date with industry trends and advancements in AI technologies, integrating new methodologies and frameworks to continually enhance the AI engineering function.
  • Contribute to creating specialized AI solutions in healthcare, leveraging domain-specific knowledge for task adaptation and :
  • Minimum education: Bachelors degree in any Engineering Stream
  • Specialized training, certifications, and/or other special requirements: Nice to have
  • Preferred education: Computer : Minimum relevant experience - 4+ years in AI AND COMPETENCIES Skills :
  • Advanced proficiency in Python with expertise in data science libraries (NumPy, Pandas, scikit-learn) and deep learning frameworks (PyTorch, TensorFlow)
  • Extensive experience with LLM frameworks (Hugging Face Transformers, LangChain) and prompt engineering techniques
  • Experience with big data processing using Spark for large-scale data analytics
  • Version control and experiment tracking using Git and MLflow
  • Software Engineering & Development: Advanced proficiency in Python, familiarity with Go or Rust, expertise in microservices, test-driven development, and concurrency processing.
  • DevOps & Infrastructure: Experience with Infrastructure as Code (Terraform, CloudFormation), CI/CD pipelines (GitHub Actions, Jenkins), and container orchestration (Kubernetes) with Helm and service mesh implementations.
  • LLM Infrastructure & Deployment: Proficiency in LLM serving platforms such as vLLM and FastAPI, model quantization techniques, and vector database management.
  • MLOps & Deployment: Utilization of containerization strategies for ML workloads, experience with model serving tools like TorchServe or TF Serving, and automated model retraining.
  • Cloud & Infrastructure: Strong grasp of advanced cloud services (AWS, GCP, Azure) and network security for ML systems.
  • LLM Project Experience: Expertise in developing chatbots, recommendation systems, translation services, and optimizing LLMs for performance and security.
  • General Skills: Python, SQL, knowledge of machine learning frameworks (Hugging Face, TensorFlow, PyTorch), and experience with cloud platforms like AWS or GCP.
  • Experience in creating LLD for the provided architecture.
  • Experience working in microservices based Expertise :
  • Strong mathematical foundation in statistics, probability, linear algebra, and optimization
  • Deep understanding of ML and LLM development lifecycle, including fine-tuning and evaluation
  • Expertise in feature engineering, embedding optimization, and dimensionality reduction
  • Advanced knowledge of A/B testing, experimental design, and statistical hypothesis testing
  • Experience with RAG systems, vector databases, and semantic search implementation
  • Proficiency in LLM optimization techniques including quantization and knowledge distillation
  • Understanding of MLOps practices for model deployment and Competencies :
  • Strong analytical thinking with ability to solve complex ML challenges
  • Excellent communication skills for presenting technical findings to diverse audiences
  • Experience translating business requirements into data science solutions
  • Project management skills for coordinating ML experiments and deployments
  • Strong collaboration abilities for working with cross-functional teams
  • Dedication to staying current with latest ML research and best practices
  • Ability to mentor and share knowledge with team members

(ref:hirist.tech)
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