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Sundew is a leading digital transformation company with a 17-year legacy of excellence that helps businesses leverage data-driven insights to drive innovation and optimize operations. We are seeking a talented Data Engineer with expertise in Robotic Process Automation (RPA) and Artificial Intelligence/Machine Learning (AI/ML) to join our dynamic team. As a Data Engineer with RPA and AI/ML expertise, you will play a crucial role in designing, implementing, and maintaining data pipelines, workflows, and automation solutions. Your responsibilities will include developing and fine-tuning LLM models with expertise in RAG (Retrieval-Augmented Generation), content extraction, and familiarity with the concept of local LLMs. Additionally, you will collaborate closely with our Data Engineering team to innovate and optimize LLM models and work with cross-functional teams to integrate RPA infrastructure, enabling clients to automate existing processes. Role & Responsibilities - Develop and optimize LLM models using state-of-the-art techniques, focusing on RAG (Retrieval-Augmented Generation). - Implement content extraction methods to enhance the accuracy and relevance of generated responses. - Collaborate with cross-functional teams to identify and address LLM development and deployment challenges. - Stay updated with the latest advancements in natural language processing (NLP) and machine learning research. - Provide technical guidance and mentorship to junior team members. - Contribute to documenting and disseminating best practices in LLM development and deployment. - Implement RPA solutions to automate repetitive tasks and improve operational efficiency. - Collaborate with data scientists and business analysts to understand data requirements and translate them into technical solutions. - Monitor performance, troubleshoot issues, and optimize data workflows for scalability and reliability. - Stay up-to-date with the latest trends and technologies in data engineering, RPA, and AI/ML. Required Skill Sets - Bachelor's or higher degree in Computer Science, Engineering, or a related field. - Proven experience in developing and fine-tuning LLM models, preferably with a focus on RAG. - Hands-on experience with RPA tools such as UiPath, Automation Anywhere, Blue Prism, Power Automate. - Strong proficiency in Python programming and familiarity with relevant libraries/frameworks such as TensorFlow, PyTorch, scikit-learn. - Solid understanding of natural language processing (NLP) fundamentals and machine learning principles. - Experience with content extraction techniques such as Named Entity Recognition (NER), text summarization, and information retrieval. - Familiarity with the concept of local LLMs and their applications in specific domains or languages. - Excellent problem-solving skills and the ability to work effectively in a collaborative team environment. - Strong communication skills with the ability to explain complex technical concepts to non-technical stakeholders. Preferred Qualifications - Experience with cloud platforms such as AWS, Azure, or Google Cloud. - Prior working knowledge in implementing RPA and AI/ML Methods. - Certification in RPA or AI/ML technologies. - Contributions to open-source projects related to natural language processing or machine learning. - Knowledge of big data technologies (e.g., Hadoop, Spark, Kafka). How To Apply Interested candidates should submit their resume and a cover letter detailing their relevant experience and explaining how they meet the specified requirements. Sundew is an equal opportunity employer. We encourage candidates of all backgrounds to apply.,

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!,