2 Language Models Jobs

Job Description: Dreaming big is in our DNA. It's who we are as a company, our culture, our heritage, and more than ever, our future. A future where we're always looking forward, serving up new ways to meet life's moments, and where we keep dreaming bigger. We look for individuals with passion, talent, and curiosity and provide them with teammates, resources, and opportunities to unleash their full potential. The power we create together, when we combine your strengths with ours, is unstoppable. Are you ready to join a team that dreams as big as you do AB InBev GCC, incorporated in 2014 as a strategic partner for Anheuser-Busch InBev, leverages the power of data and analytics to drive growth for critical business functions such as operations, finance, people, and technology. The teams are transforming Operations through Tech and Analytics. Do you dream big We need you. Job Title: Senior Data Scientist Location: Bangalore Reporting to: Senior Manager Purpose of Role: - Understand and solve complex business problems with sound analytical prowess to provide impactful insights in decision-making. - Ensure any implementation roadblocks are communicated to the Analytics Manager to prevent project timeline delays. - Document every aspect of the project in a standard way for future reference. - Articulate technical complexities to senior leadership in a simple and easy-to-understand manner. Key Tasks and Accountabilities: - Understand business problems and collaborate with stakeholders to translate them into data-driven analytical/statistical problems during the solution-building process. - Create appropriate datasets and develop statistical data models. - Translate complex statistical analyses over large datasets into insights and actionable steps. - Analyze results and present findings to stakeholders. - Communicate insights using business-friendly presentations. - Mentor other Data Scientists/Associate Data Scientists. - Build a project pipeline in Databricks that is production-ready. - Develop dashboards (preferably in Power BI) for easy consumption of solutions. Qualifications, Experience, Skills: - Level of Educational Attainment Required: Bachelor's/Master's Degree in Statistics, Applied Statistics, Economics, Econometrics, Operations Research, or any other quantitative discipline. - Previous Work Experience: Minimum 4-6 years in a data science role, building, implementing, and operationalizing end-to-end solutions. - Expertise strongly desired in building statistical and machine learning models for classification, regression, forecasting, anomaly detection, dimensionality reduction, clustering, etc. - Exposure to optimization and simulation techniques (good to have). - Expertise in building NLP-based language models, sentiment analysis, text summarization, and Named Entity Recognition. - Proven skills in translating statistics into insights, with sound knowledge in statistical inference and hypothesis testing. - Mandatory: Microsoft Office, Expert in Python, Advanced Excel. - An undying love for beer!,

As a Manager, Machine Learning Engineering, you will collaborate with cross-functional teams to strategize, develop, and deliver machine learning models tailored to meet specific business objectives. You will be responsible for overseeing the entire lifecycle of these models, from data preprocessing and algorithm selection to performance evaluation and seamless integration into production systems. This role has a specific focus on Generative AI . Your Impact: What You'll Achieve As a Manager, Data Science specializing in Generative AI, you will: Lead AI-Driven Innovations: Drive the development of state-of-the-art AI and machine learning solutions that transform business strategies and deliver exceptional customer experiences. Strategic Collaboration: Work closely with cross-functional teams, including product managers, data engineers, and business stakeholders, to define and execute data-driven solutions aligned with organizational goals. Foster a High-Performance Team: Build, mentor, and lead a team of talented data scientists, cultivating a culture of innovation, collaboration, and continuous learning. Deliver Business Impact: Translate complex business problems into AI/ML solutions by leveraging advanced techniques such as generative AI, deep learning, and NLP , ensuring measurable outcomes. Optimize AI Pipelines: Oversee the development and deployment of scalable, efficient, and robust machine learning pipelines that address latency, responsiveness, and real-time data processing challenges. Customize AI Models: Direct the customization and fine-tuning of AI models, including large language models (LLMs) and other generative AI technologies, to meet domain-specific requirements. Promote Data-Driven Decision-Making: Advocate for data-centric approaches across teams, ensuring data quality, integrity, and readiness to maximize model performance and business impact. Develop Intelligent AI Agents: Architect and refine AI agents that solve complex business challenges, leveraging LLMs to deliver personalized, user-centric solutions. Advance Generative AI Applications: Innovate with cutting-edge generative AI models such as LLM, VLM, GANs, and VAEs to create tailored applications for dynamic content creation, predictive analytics, and enhanced automation. Scale AI with Cloud Technology: Deploy and scale LLM-based solutions on platforms like GCP, AWS, and Azure to address real-world business problems with precision and efficiency. Stay at the Cutting Edge: Keep up-to-date with emerging trends and innovations in AI and data science, identifying opportunities to incorporate the latest advancements into projects. Responsibilities Design AI Systems: Build AI agents for tasks such as content compliance, asset decomposition, and contextual personalization. Develop NLP Pipelines: Implement advanced NLP solutions for search relevance, intent detection, and dynamic content generation. Integrate Multi-Modal Systems: Combine data modalities such as text, images, and metadata for enriched user interactions and insights. Optimize AI Pipelines: Innovate in latency reduction, scalability, and real-time responsiveness for AI systems in production. Collaborate on AI Innovation: Work with business stakeholders to identify opportunities and deliver impactful AI-driven solutions. Qualifications Your Skills & Experience Overall Experience: 8 to 15 years of experience. Generative AI Experience: At least 2 years of Gen AI experience . LLM Fine-tuning: Fine-tuning experience with Large Language Models (LLMs, VLLMs, or Vision models) . Distributed Training/Inference: Experience with distributed training or inference frameworks like Ray, vllm, openllm, bentoML etc. Generative AI Frameworks: Experience with frameworks like LangChain, Llamaindex for building maintainable, scalable Generative AI applications. LLM Deployment/Optimization: Deployment experience or optimized hosting experience of Large Language Models (LLMs, VLLMs, or Vision models) . Vector Databases: Experience working with any Vector database like Milvus, FAISS, ChromaDB etc. Agent Development: Experience developing agents with frameworks like LangGraph, CrewAI, Autogen etc. Prompt Engineering: Experience with prompt engineering. Market Trends: Keeping up with latest market trends. Open Source LLMs: Experience working with open-source large language models from HuggingFace . Cloud Providers: Experience working with at least one public cloud provider such as Azure, AWS, or GCP . Container Technology: Experience working with container technology like Docker, ECS etc. DevOps & CI/CD: Experience with DevOps practices and CI/CD pipelines for data solutions. Production Deployment: Experience in deploying solutions to production with Kubernetes or OpenShift . ML Workflow Management: Experience with managing ML workflows with MLFlow or KubeFlow.