Goldman Sachs Recruitment 2023 Details:
What We Do
At Goldman Sachs, our Engineers don’t just make things – we make things possible. Change the world by connecting people and capital with ideas. Solve the most challenging and pressing engineering problems for our clients. Join our engineering teams that build massively scalable software and systems, architect low latency infrastructure solutions, proactively guard against cyber threats, and leverage machine learning alongside financial engineering to continuously turn data into action. Create new businesses, transform finance, and explore a world of opportunity at the speed of markets.
Engineering, which is comprised of our Technology Division and global strategists’ groups, is at the critical center of our business, and our dynamic environment requires innovative strategic thinking and immediate, real solutions. Want to push the limit of digital possibilities? Start here.
Official Website: www.goldmansachs.com
Job Profile: Natural Language Processing – Software Engineer – Associate – Bengaluru
Salary: Not Disclosed
Experience Required: Experienced
Job Location: Bangalore
Who We Look For
Goldman Sachs Engineers are innovators and problem-solvers, building solutions in risk management, big data, mobile and more. We look for creative collaborators who evolve, adapt to change and thrive in a fast-paced global environment.
We are a leading financial firm specializing in providing innovative solutions to our clients. We are seeking a talented and experienced Senior AI Engineer to join our team and lead efforts in the design and implementation of generative AI solutions. We are specifically looking for someone with hands-on expertise in natural language processing (NLP) and Large Language Models (LLMs) and a passion to solve hard problems on unique financial datasets. This role will focus on implementing end-to-end solutions in the areas of search and information retrieval (IR); question answering and conversational AI; document summarization; entity, event, and relationship extraction and classification; as well as structured text extraction from documents.
Core Responsibilities:
- Search and Retrieval:
- Utilize your expertise in language models to improve search and retrieval algorithms.
- Conduct thorough experiments and evaluate different AI models for various use cases.
- Select and implement the most suitable AI models for improving search and retrieval performance
- Conversational AI:
- Develop conversational AI services using large language models to enable interactions such as question answering and summarization
- Leverage open source language models (LLMs) and/or proprietary models and vendor platforms like Google/Microsoft/OpenAI to effectively solve customer problems
- Collaborate with cross-functional teams, including UX/UI designers, to deliver exceptional user experiences to stakeholders
- Model Development and Training:
- Build and train working versions of AI models using the GS NLP platform
- Leverage your knowledge of machine learning techniques to optimize and enhance the performance of the model
- Collaborate with the data engineering team to ensure efficient data pipelines for model training and push innovative deep learning models to production
- Reusable Patterns, Libraries, and Datasets:
- Identify and create reusable patterns, model catalogs, and datasets to improve efficiency and accelerate development
- Contribute to the company’s internal knowledge base by documenting best practices and sharing insights with the team
Requirements:
- Undergraduate/graduate degree in Computer Science or related fields
- Proven experience in hands-on machine learning development, in a financial firm or a similar industry
- Strong expertise in AI models and machine learning techniques, particularly in latest language models
- Experience with language modeling, prompt tuning and engineering, instruction tuning, and/or RLHF
- Experience with AI platforms and frameworks, such as TensorFlow, PyTorch, Keras, HuggingFace
- Experience with search and retrieval algorithms, conversational AI, and large-scale document AI techniques
- Excellent communication and collaboration skills to work effectively in a cross-functional team
- Demonstrated experience in driving business-critical projects using agile methodologies and best practices in software engineering
- Experience in Docker Containerization, K8s, API gateway, Software Load Balancer, gitlab CI/CD Pipeline, Observability tools like Prometheus. Build and enhance orchestration tools to enable semantic search data ingestion pipelines that will be used in document ingestion, vector embeddings for document digitization, search and retrieval and conversational services.
Apply Before the link Expires for Goldman Sachs Recruitment 2023.
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