Compliance, New York, Vice President, AL/ML Engineer

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    "ExternalDescriptionStr": "<p style=\"margin-left:0in\"><b>VP - AI/ML Engineer - Compliance Engineering</b></p>\n<p style=\"margin-left:0in\"><b>YOUR IMPACT</b></p>\n<p style=\"margin-left:0in\">Are you passionate about leveraging cutting-edge AI/ML techniques, including Large Language Models, to solve complex, mission-critical problems in a dynamic environment? Do you want to contribute to safeguarding a leading global financial institution?</p>\n<p style=\"margin-left:0in\"><b>OUR IMPACT</b></p>\n<p style=\"margin-left:0in\">We are Compliance Engineering, a global team of engineers and scientists dedicated to preventing, detecting, and mitigating regulatory and reputational risks across Goldman Sachs. We build and operate a suite of platforms and applications that protect the firm and its clients.</p>\n<p style=\"margin-left:0in\">We offer:</p>\n<ul>\n <li>Access to petabyte scale&nbsp;of structured and unstructured data to fuel your AI/ML models, including textual data suitable for LLM applications.</li>\n <li>The opportunity to work with state-of-the-art LLM models and agentic framework.</li>\n <li>A collaborative environment where you can learn from and contribute to a team of experienced engineers and scientists.</li>\n <li>The chance to make a tangible impact on the firm's ability to manage risk and maintain its reputation.</li>\n</ul>\n<p style=\"margin-left:0in\">Within Compliance Engineering, we are seeking an experienced AI/ML Engineer to join our Engineering team. This role will focus on solving highly complex business problems using AI/ML techniques, incorporating latest emerging trends om building out vertical AI agents to run on data at massive scale.&nbsp;</p>\n<p style=\"margin-left:0in\"><b>HOW YOU WILL FULFILL YOUR POTENTIAL</b></p>\n<p style=\"margin-left:0in\">As a member of our team, you will:&nbsp;</p>\n<ul>\n <li>Design and architect scalable and reliable end-to-end AI/ML solutions specifically tailored for compliance applications, ensuring adherence to relevant regulatory requirements. This encompasses the development and implementation of GenAI-driven solutions, including agentic frameworks for automating compliance processes, RAG pipelines, and the creation and utilization of embeddings for compliance knowledge bases.</li>\n <li>Explore diverse AI/ML problems, such as model fine-tuning, prompt engineering, and experimentation with different algorithmic approaches to address novel business challenges.</li>\n <li>Develop, test, and maintain high-quality, production-ready code.</li>\n <li>Lead technical projects from inception to completion, providing guidance and mentorship to junior engineers.</li>\n <li>&nbsp;Collaborate effectively with compliance officers, legal counsel, and other stakeholders to understand business requirements and translate them into technical solutions.&nbsp;</li>\n <li>Participate in code reviews to ensure code quality, maintainability, and adherence to coding standards. Promote best practices for AI/ML development, including version control, testing, and documentation.</li>\n <li>Stay current with the latest advancements in AI/ML platforms, tools, and techniques to solve business problems.&nbsp;</li>\n</ul>\n<p style=\"margin-left:0in\"><b>QUALIFICATIONS</b></p>\n<p style=\"margin-left:0in\">A successful candidate will possess the following attributes:</p>\n<ul>\n <li>A Bachelor's, Master's or PhD degree in Computer Science, Machine Learning, Mathematics, or a similar field of study.</li>\n <li>Preferably 7+ years AI/ML industry experience for Bachelor’s/Masters, 4+ years for PhD with a focus on Language Models.</li>\n <li>Strong foundation in machine learning algorithms, including deep learning architectures (e.g., transformers, RNNs, CNNs)</li>\n <li>Proficiency in Python and relevant libraries/frameworks such as TensorFlow, PyTorch, Hugging Face Transformers, scikit-learn.</li>\n <li>Demonstrated expertise in GenAI techniques, including but not limited to Retrieval-Augmented Generation (RAG), model fine-tuning, prompt engineering, AI agents, and evaluation techniques.</li>\n <li>Experience working with embedding models and vector databases.</li>\n <li>Experience with MLOps practices, including model deployment, containerization (Docker, kubernetes), CI/CD, and model monitoring.</li>\n <li>Strong verbal and written communication skills.</li>\n <li>Curiosity, ownership and willingness to work in a collaborative environment.</li>\n <li>Proven ability to mentor and guide junior engineers.</li>\n</ul>\n<p>&nbsp;</p>\n<p>Experience in some of the following is desired and can set you apart from other candidates:</p>\n<ul>\n <li>Experience with Agentic Frameworks (e.g., Langchain, AutoGen) and their application to real-world problems.</li>\n <li><span>Understanding of scalability and performance optimization techniques for real-time inference such as quantization, pruning, and knowledge distillation.</span></li>\n <li>Experience with model interpretability techniques.</li>\n <li>Prior experience in code reviews/ architecture design for distributed systems.</li>\n <li>Experience with data governance and data quality principles.</li>\n <li>Familiarity with financial regulations and compliance requirements.</li>\n</ul>\n<p>&nbsp;</p>\n<p>&nbsp;</p>\n<p>&nbsp;</p>\n<p>&nbsp;</p>",
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