5 Azure Mlops Jobs

You will be part of a rapidly growing team at NPS Prism, a technology-led business venture owned by Bain & Company, located in Gurugram. As a Data Scientist specializing in Large Language Models (LLMs), your role will involve developing and deploying innovative solutions to address various business challenges using cutting-edge machine learning techniques. You will collaborate with cross-functional teams to identify use cases for LLM applications and work towards building a robust analytics architecture. Staying updated with the latest advancements in LLMs and NLP will be a key part of your responsibilities, along with analyzing complex data to derive actionable insights. Your qualifications should include a Bachelor's or Master's degree in computer science, Data Science, Statistics, or a related field, along with 4+ years of experience in data science with a focus on natural language processing and LLMs. Proficiency in Python & PySpark, experience with machine learning frameworks like TensorFlow, PyTorch, and Hugging Face Transformers, as well as cloud computing platforms such as AWS, Google Cloud, Azure, are essential. Strong problem-solving skills, the ability to communicate technical concepts effectively, and experience in a fast-paced startup environment are also required. In this role, you will lead the development and deployment of LLM-based solutions, design and optimize machine learning models, mentor junior data scientists, and ensure the scalability and robustness of LLM solutions in production environments. You will be expected to take ownership of projects end-to-end, operate in ambiguous situations, and deliver results within ambitious timelines. Your contribution to code reviews and continuous improvement of ML infrastructure and practices will be crucial for the team's success. By joining NPS Prism, you will have the opportunity to work on groundbreaking projects, collaborate with talented individuals, and drive business growth to new heights. If you are a self-motivated individual with a passion for data science and a drive to excel in a challenging environment, we encourage you to apply and be part of our journey towards shaping the future of customer experience benchmarking and operational improvement.,

As a Senior Data Scientist at NPS Prism, you will play a crucial role in guiding and coaching junior Data Scientists in technical and storytelling aspects. Your expertise will be instrumental in leading the development, deployment, and adoption of open source LLM models for text classification, as well as building sentiment models. Additionally, you will spearhead the development, deployment, and adoption of causal inference models to measure marketing campaigns and optimize investments across short and long-term business objectives. Collaboration will be a key aspect of your role as you work closely with Data Engineering, Product, and Technology teams to further build out the analytics architecture. Taking ownership of end-to-end projects, you will operate in situations with a high degree of ambiguity and deliver results within ambitious timelines. Your ability to translate insights into relevant business recommendations will be essential in anticipating the needs of business stakeholders. To excel in this role, you should possess a Bachelor's degree in computer science or equivalent experience, along with 6 to 10 years of Data Science experience covering ML, DL, and GenAI. Proficiency in building end-to-end data science applications using dash, Flask, Streamlit, and Django is preferred. Experience in NLP and LLM fine-tuning, cultural transformation to CI/CD and MLOps, Azure MLOps or other SDLC tools, Agile methodologies, and building applications using fast APIs will be highly advantageous. Previous experience in a startup, fast-growth, rapid-change environment, along with self-motivation, dedication to quality, and a commitment to doing the right thing are key attributes for success in this role. Preferred qualifications include experience with HTML, CSS, JavaScript, version control using Git, Containers, Kubernetes, TensorFlow, Pytorch, and other relevant technologies. By joining NPS Prism, you will have the opportunity to be part of a dynamic team that is shaping the future of customer experiences and driving business growth to its full potential.,

Role & responsibilities: Looking for 5 to 8 years experience of ML Engineer with strong Azure Cloud DevOps with even stronger DABs DevOps skills with even stronger DABs Databricks Asset Bundles implementation knowledge. 1 Azure Cloud Engineer 2 Azure DevOps CICD experienced in DABs 3 ML Engineer for deployment Translate business requirement into technical solution Implementation of MLOPS Scalable solution using AIML and reduce the risk of Fraud and other fiscal crisis Creating MLOPS Architecture and implementing it for multiple models in a scalable and automated way Designing and implementing end to end ML solutions Operationalize and monitor machine learning models using high end tools and technologies Design implementation of DevOps principles in Machine Learning Data Science quality assurance and testing Collaborate with data scientists engineers and other key stakeholders Preferred candidate profile: Azure Cloud Engineering Design implement and manage scalable cloud infrastructure on Microsoft Azure Ensure high availability performance and security of cloud based applications Collaborate with cross functional teams to define and implement cloud solutions Azure DevOps CICD Develop and maintain CICD pipelines using Azure DevOps Automate deployment processes to ensure efficient and reliable software delivery Monitor and troubleshoot CICD pipelines to ensure smooth operation DABs Databricks Asset Bundles Implementation Lead the implementation and management of Databricks Asset Bundles Optimize data workflows and ensure seamless integration with existing systems Provide expertise in DABs to enhance data processing and analytics capabilities Machine Learning Deployment Deploy machine learning models into production environments Monitor and maintain ML models to ensure optimal performance Collaborate with data scientists and engineers to integrate ML solutions into applications.

8+ years of total experience with 5+ years of professional experience in AI, ML or a related field. Master's or PhD in Computer Science, Mathematics, AI or a related field. Good mathematical understanding of machine learning and deep learning algorithms. Advanced knowledge of statistical and algorithmic models as well as of fundamental mathematical concepts, such as linear algebra and probability. Experience with Natural Language Processing, Deep Learning, and Computer Vision techniques. Proficiency in programming languages such as Python or Scala, along with experience using DL frameworks like TensorFlow, PyTorch etc. Experience working with large data sets and writing efficient code capable of processing large data streams at speed. Experience in program leadership, governance, and change enablement Understand client challenges and propose solutions based on AI/GenAI capabilities. Analyze and explain AI and machine learning (ML) solutions while setting and maintaining high ethical standards. Work on functional design, process design, prototyping, testing, training, and defining support procedures, in collaboration with data engineering team and executive leadership. Train and deploy AI models to solve complex business problems or automate processes. Convert AI/ML models into APIs to be used in other applications. Manage a team in implementing AI solutions and developing products. Collaborate with external partners, such as research institutions or universities, to explore innovative AI approaches and foster collaborative research projects. Ensure compliance with data privacy regulations and ethical guidelines while working with sensitive and confidential data. Stay up to date with the latest developments in machine learning and AI. Experience working with Azure Data & AI services. Experience with MLOps tools like MLFLow, Azure MLOps or similar tools. High level of ownership and creative problem solving under resource constraints. Excellent verbal and written communication skills. Ability to interact with C-Level executives

Job Summary: We are seeking a highly skilled MLOps Engineer to design, deploy, and manage machine learning pipelines in Google Cloud Platform (GCP). In this role, you will be responsible for automating ML workflows, optimizing model deployment, ensuring model reliability, and implementing CI/CD pipelines for ML systems. You will work with Vertex AI, Kubernetes (GKE), BigQuery, and Terraform to build scalable and cost-efficient ML infrastructure. The ideal candidate must have a good understanding of ML algorithms, experience in model monitoring, performance optimization, Looker dashboards and infrastructure as code (IaC), ensuring ML models are production-ready, reliable, and continuously improving. You will be interacting with multiple technical teams, including architects and business stakeholders to develop state of the art machine learning systems that create value for the business. Responsibilities: Managing the deployment and maintenance of machine learning models in production environments and ensuring seamless integration with existing systems. Monitoring model performance using metrics such as accuracy, precision, recall, and F1 score, and addressing issues like performance degradation, drift, or bias. Troubleshoot and resolve problems, maintain documentation, and manage model versions for audit and rollback. Analyzing monitoring data to preemptively identify potential issues and providing regular performance reports to stakeholders. Optimization of the queries and pipelines. Modernization of the applications whenever required Qualifications: Expertise in programming languages like Python, SQL Solid understanding of best MLOps practices and concepts for deploying enterprise level ML systems. Understanding of Machine Learning concepts, models and algorithms including traditional regression, clustering models and neural networks (including deep learning, transformers, etc.) Understanding of model evaluation metrics, model monitoring tools and practices. Experienced with GCP tools like BigQueryML, MLOPS, Vertex AI Pipelines (Kubeflow Pipelines on GCP), Model Versioning & Registry, Cloud Monitoring, Kubernetes, etc. Solid oral and written communication skills and ability to prepare detailed technical documentation of new and existing applications. Strong ownership and collaborative qualities in their domain. Takes initiative to identify and drive opportunities for improvement and process streamlining. Bachelors Degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience. Bonus Qualifications: Experience in Azure MLOPS, Familiarity with Cloud Billing. Experience in setting up or supporting NLP, Gen AI, LLM applications with MLOps features. Experience working in an Agile environment, understanding of Lean Agile principles.