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 deployment.QUALIFICATION :- Minimum education:



Bachelors degree in any Engineering Stream- Specialized training, certifications, and/or other special requirements: Nice to have- Preferred education: Computer Science/Engineering.EXPERIENCE : Minimum relevant experience - 4+ years in AI EngineeringSKILLS AND COMPETENCIES :Technical 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:



Solid 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 architecture.Domain 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 monitoringProfessional 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)

📌 Data Scientist - Artificial Intelligence/Machine Learning (Hyderabad)
🏢 Techno Comp Computer Services
📍 Hyderabad