Valiance Solutions - LLMOps Engineer

About Us : Valiance is a global AI & Data analytics firm helping clients build cutting-edge technology solutions for digital transformation. We work with some of the marquee brands across India, US and APAC to build transformative solutions for Credit Risk, Fraud, Predictive Maintenance, Quality Inspection, Data lake, IOT analytics etc. Our team comprises 120 professionals across Machine Learning, Data Engineering & Cloud expertise Required Technical and Professional Expertise : As an LLMOps Engineer, you will play a critical role in the development, deployment, and maintenance of large language models (LLMs) in production environments. Your work will ensure that our models are scalable, efficient, and meet the highest performance standards. You will collaborate with data scientists, ML engineers, and software developers to optimize LLM pipelines, manage model lifecycle, and ensure robust monitoring and governance. Key Responsibilities : - Design, implement, and manage LLM workflows for training and inference. - Collaborate with cross-functional teams to understand model requirements and integrate LLM solutions. - Monitor model performance, conduct A/B testing, and implement improvements based on user feedback and analytics. - Maintain and optimize cloud-based infrastructure for scalability and cost-efficiency. - Develop and implement best practices for version control, testing, and deployment of LLMs. - Automate repetitive tasks related to model training, deployment, and monitoring. - Provide technical support and troubleshooting for deployed models and systems. - Stay updated on the latest trends and advancements in LLM technologies and ML operations. Qualifications : - Bachelor's degree in Computer Science, Engineering, or a related field; Master's degree preferred. - 1 years of experience in machine learning operations (MLOps), with a strong focus on LLMs. - Proficiency in programming languages such as Python and familiarity with ML frameworks like TensorFlow, PyTorch, or Hugging Face. - Experience with containerization and orchestration tools, such as Docker and Kubernetes. - Knowledge of cloud platforms (AWS, Azure, GCP) and related tools for deploying and managing ML models. - Strong understanding of data pipelines, ETL processes, and data management for training LLMs. - Familiarity with version control systems (e.g., Git) and CI/CD workflows. - Excellent problem-solving skills and ability to work collaboratively in a team environment. Preferred Skills : - Experience with NLP tasks and relevant libraries (e.g., spaCy, NLTK). - Understanding of model interpretability and ethical considerations in AI. - Familiarity with monitoring tools for model performance and operational insights (e.g., Prometheus, Grafana). (ref:hirist.tech)

Location: in, IN

Posted Date: 5/9/2025