Machine Learning Engineer - Document Digitization (LLMs)-Vice PresidentTwinThread LLC • Jersey City, New Jersey, United States

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Machine Learning Engineer - Document Digitization (LLMs)-Vice President

TwinThread LLC

Jersey City, New Jersey, United States

Jersey City, New Jersey, United States

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Are you passionate about leveraging advanced technology to solve complex business challenges? As an applied AI/ML, you will have the opportunity to shape the future of document management through cutting‑edge AI and machine learning. Join a collaborative team where your expertise will drive impactful solutions and strategic outcomes. This role offers a platform to innovate, lead, and make a difference across the organization. As a Machine Learning Engineer – Document Digitization (LLMs)-Vice President in our organization, you will design, develop, and deploy secure, scalable, and innovative technology products that transform how documents are processed and managed. You will use advanced AI and machine learning to extract, analyze, and manage information, driving strategic business outcomes. You will collaborate with cross‑functional teams, mentor others, and continuously seek opportunities for improvement and innovation. Job responsibilities Lead the design, development, and integration of AI‑powered document digitization solutions, focusing on extracting information and insights from diverse document types. Manage the end‑to‑end AI/ML lifecycle: model training, validation, deployment, monitoring, and continuous improvement in production environments. Employ generative AI, and large language models (LLMs) to automate and optimize document workflows. Build and maintain scalable document digitization pipelines using Python, AI frameworks, and cloud technologies. Provision and manage cloud resources using infrastructure as code tools (Terraform) and AWS services (SageMaker, Bedrock). Ensure scalability, reliability, security, and compliance of AI/ML solutions, adhering to best practices and governance standards. Collaborate with cross‑functional teams to reimagine legacy document processing systems using generative AI and LLMs. Develop and maintain dashboards and reporting tools to monitor digitization accuracy, workflow efficiency, and business impact. Mentor junior engineers and promote best practices in AI/ML, software engineering, and testing. Conduct model validation, human‑in‑the‑loop review, and implement continuous improvement strategies for digitization accuracy. Contribute to communities of practice and explore new and emerging technologies. Required qualifications, capabilities, and skills Bachelor’s or Master’s in Computer Science, Data Science, Machine Learning, or related field, with relevant industry experience. Strong proficiency in Python programming; familiarity with Java and front‑end technologies (React.JS, AngularJS). Hands‑on experience with AI/ML model development, deployment, and MLOps practices in production environments. Expertise in machine learning frameworks (TensorFlow, PyTorch, Scikit‑learn, PyTorch Lightning). Knowledge of generative AI models (GANs, VAEs, transformers, diffusion models) and LLMs. Experience with AWS cloud platforms (SageMaker, Bedrock), containerization (Docker, Kubernetes, Amazon EKS), and infrastructure as code (Terraform). Familiarity with NoSQL databases (Mongo Atlas, ElasticSearch, OpenSearch, Neo4J). Experience with agentic coding approaches, autonomous code agents, and last sprinting code generation. Strong understanding of SDLC, CI/CD, resiliency, and security practices. Demonstrated ability to accelerate development using AI technologies. Experience deploying and maintaining AI/ML solutions in large‑scale, production environments and strong problem‑solving, communication, and collaboration skills. Preferred qualifications, capabilities, and skills Experience in financial services, especially investment banking or credit risk operations. Expertise in agentic AI frameworks, prompt optimization, and fine‑tuning SLMs. Familiarity with distributed computing, data sharing, and DDP training. Experience in design/code reviews and mentoring teams. AWS Generative AI Developer Professional certification or equivalent. We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission‑based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on‑site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans. Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we’re setting our businesses, clients, customers and employees up for success. Lead AI/ML engineer to build secure GenAI/LLM document digitization pipelines on AWS, with end‑to‑end MLOps leadership.
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Jersey City, New Jersey, United States

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English

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