Data Scientist Artificial Intelligence/Machine Learning

Job description

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

Required Skill Profession

Mathematical Science Occupations