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Louis Vuitton

<div>
 
 About The Job
 
 
 
 Louis Vuitton Americas is seeking a Senior Data Scientist &ndash; Analytics and AI Data to join our Digital team based in New York City. This individual will act as a hybrid data scientist, MLOps engineer, BI SME, business analyst, and data engineer, while owning the roadmap of analytics and AI solutions that can be industrialized and scaled by central teams. You will sit at the intersection of local business needs and global data/AI strategy, ensuring solutions are impactful, scalable, and aligned with enterprise priorities.
 
 
 Job responsibilities
 
 
 <ul>
 <li>
 Product Strategy &amp; Cross-Functional Roadmap:
 
 </li>
 <ul>
 <li>
 Lead the comprehensive analytics and AI roadmap, guiding it from opportunity identification and prioritization through delivery and transition to central teams.
 </li>
 <li>
 Collaborate with diverse functional stakeholders (e-commerce, retail, CRM, supply chain, finance, etc.) to identify use cases, define problem statements, and translate these into clear data product requirements.
 </li>
 <li>
 Establish success metrics, measure value realization, and continuously refine the roadmap based on impact and feedback.
 
 </li>
 </ul>
 <li>
 Data Science &amp; Advanced Analytics:
 
 </li>
 <ul>
 <li>
 Design and lead predictive models and analytical solutions utilizing Python and SQL.
 </li>
 <li>
 Conduct thorough exploratory data analysis, feature engineering, model training, validation, and comprehensive documentation.
 </li>
 <li>
 Develop reusable analytical assets (scores, segments, KPIs) for broad application across various markets and functions.
 
 </li>
 </ul>
 <li>
 MLOps &amp; Data Engineering:
 
 </li>
 <ul>
 <li>
 Collaborate with MLOps and Data Engineering teams to develop, orchestrate, and maintain robust data and machine learning pipelines, leveraging tools such as Dataiku and Google BigQuery.
 </li>
 <li>
 Implement best practices for testing, version control, monitoring, and observability to ensure the creation of reliable, production-grade solutions.
 </li>
 <li>
 Partner with central data engineering and platform teams to align initiatives with enterprise standards and promote scalability.
 </li>
 <li>
 Work alongside business, local, and central Data Engineering teams to facilitate data integration and validation, effectively addressing diverse business challenges.
 
 </li>
 </ul>
 <li>
 BI, Insights &amp; Business Analysis:
 
 </li>
 <ul>
 <li>
 Act as a Business Intelligence Subject Matter Expert, contributing to the definition of semantic layers, Key Performance Indicators (KPIs), and data models that enable self-service analytics.
 </li>
 <li>
 Guide or develop insightful dashboards and reports using tools like Power BI, Tableau, or Looker, ensuring their actionability and broad adoption across the organization.
 </li>
 <li>
 Perform business analysis, meticulously gathering requirements, mapping processes, and transforming analytical findings into clear recommendations and compelling narratives for various stakeholders.
 
 </li>
 </ul>
 <li>
 Collaboration with Central / Global Teams:
 
 </li>
 <ul>
 <li>
 Prepare and package local or cross-functional solutions, including code, design specifications, documentation, and KPIs, for industrialization and ongoing maintenance by central teams.
 </li>
 <li>
 Contribute to the continuous evolution of global data and AI standards, reference architectures, and best practices.
 </li>
 <li>
 Represent cross-functional analytics and AI needs in global forums, effectively highlighting dependencies, potential risks, and opportunities for scaling solutions.
 
 
 </li>
 </ul>
 </ul>
 Profile
 
 
 We are excited to speak to skilled and experienced data professional with 3+ years of hands-on experience in data science, analytics, or data engineering, demonstrating end-to-end ownership of data products. The ideal candidate will possess strong proficiency in Python (pandas, NumPy, scikit-learn), advanced SQL skills, and experience with cloud data warehouses such as Google BigQuery. Practical experience with enterprise data processing platforms like Dataiku is also essential. Candidates should have demonstrated expertise in at least three of the following areas: data science/machine learning, BI/reporting and metric design, business analysis/stakeholder management, data engineering/data processing, or Gen AI/Agentic AI product deployment. Strong communication and storytelling abilities are crucial for fostering collaboration between business and technical teams.
 
 
 Preferred qualifications include experience in retail, luxury, fashion, or consumer environments, familiarity with experimentation (A/B testing), customer analytics (segmentation, propensity, churn, LTV), or marketing attribution. Exposure to Generative AI/LLMs and their application to customer experience and productivity, along with experience in a hub-and-spoke operating model, are also highly valued. Core competencies for this role include transversal product thinking, technical breadth spanning data science, MLOps, BI, data analysis, and data engineering, the ability to lead initiatives effectively across functions and geographies, and a strong outcome orientation focused on measurable business value and long-term maintainability.
 
 
 The appointed candidate will be offered a base salary within the range USD $140,000 - $160,000, a comprehensive benefits package including: medical, dental, vision, short and long-term disability, various paid time off programs, employee discount/perks and two retirement plans both with employer contributions.
 
 
 <ul>
 <li>
 Please note that restrictions may apply to part-time employees
 
 
 </li>
 </ul>
 
 The position requires 4 days per week on site in the Louis Vuitton Corporate Office, located in the heart of Midtown, Manhattan.
 
 
 
 Additional information
 
 
 Louis Vuitton is a company that respects the uniqueness of each employee and offers everyone the means to find their place and prosper. We promote initiatives aimed at supporting professional equality for everyone. We strive to go above and beyond purely symbolic measures by building a culture passionate about meaningful strategies aimed at crafting an inclusive workforce.
 
 
 In addition to a generous benefits package, unparalleled career development opportunities, both locally &amp; globally, as an employee at Louis Vuitton, you can expect to be provided with industry leading training which will offer you an in-depth insight into the luxury and retail environment.
 
 
 Reference LVM32143
</div>

Senior Data Scientist – Analytics and AI Data

JPMorganChase

<div>JOB DESCRIPTION 
Design and deliver market-leading technology products in a secure and scalable way as a seasoned member of an agile team
As a Software Engineer III (Machine Learning Platform Engineer) at JPMorgan Chase within the Consumer &amp; Community Banking (CCB) line of business, you serve as a seasoned member of an agile team focused on building, scaling, and maintaining robust machine learning platforms. You will design and deliver trusted, market-leading infrastructure and tools that empower data scientists and ML engineers to develop, deploy, and monitor models efficiently and securely. You are responsible for implementing critical technology solutions across multiple technical areas to support the firm&rsquo;s business objectives and drive innovation in ML platform capabilities.
Job responsibilities<ul><li>
Design, build, and maintain scalable machine learning platforms and infrastructure to support end-to-end ML workflows.</li><li>
Develop and optimize tools for model training, deployment, monitoring, and lifecycle management.</li><li>
Integrate data engineering, feature management, and model serving capabilities into unified ML platform solutions.</li><li>
Implement secure, high-quality production code for platform services, APIs, and automation pipelines.</li><li>
Collaborate with data scientists, ML engineers, and product teams to understand requirements and deliver platform features that accelerate ML development and operations.</li><li>
Ensure platform reliability, scalability, and performance through proactive monitoring, troubleshooting, and continuous improvement.</li><li>
Produce architecture and design artifacts for platform components, ensuring alignment with enterprise standards and best practices.</li><li>
Automate infrastructure provisioning, configuration, and CI/CD pipelines for ML platform services.</li><li>
Contribute to the ML platform engineering community of practice and participate in events that explore new and emerging technologies.</li></ul>
Required qualifications, capabilities, and skills<ul><li>
Formal training or certification on software engineering concepts and 3+ years applied experience</li><li>
Hands-on experience building, deploying, and maintaining machine learning platforms or infrastructure</li><li>
Proficiency in Python and one or more ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
</li><li>Experience with data processing frameworks and tools (e.g., Spark, Pandas, SQL)
</li><li>Practical experience with cloud-based ML platforms (e.g., AWS SageMaker, GCP AI Platform, Azure ML) or on-prem ML infrastructure</li><li>
Strong understanding of MLOps practices, including CI/CD for ML, model versioning, and monitoring</li><li>
Experience developing APIs and platform services for ML workflows
</li><li>Solid knowledge of the software development life cycle and agile methodologies
</li><li>Ability to collaborate with cross-functional teams to deliver platform solutions aligned with business objectives
</li></ul>Preferred qualifications, capabilities, and skills<ul><li>
Familiarity with Databricks for scalable data engineering and ML platform integration</li><li>
Experience working with Snowflake for cloud-based data warehousing and analytics</li><li>
Exposure to Snorkel AI for programmatic data labeling and training data management</li><li>
Experience with containerization and orchestration tools (e.g., Docker, Kubernetes, Airflow)</li><li>
Familiarity with feature stores, model registries, and ML metadata management</li><li>
Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation)</li><li>
Experience with RESTful APIs and microservices architectures</li></ul>
ABOUT US 
Chase is a leading financial services firm, helping nearly half of America&rsquo;s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
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&rsquo; and employees&rsquo; religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Equal Opportunity Employer/Disability/Veterans 
 
 
ABOUT THE TEAM 
<div>
Our Consumer &amp; Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We&rsquo;re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions &ndash; all while ranking first in customer satisfaction.</div><div> 
 
</div><div>The CCB Data &amp; Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.</div></div>

Software Engineer III - Machine Learning Platform

Biohub

<div>
 Biohub is the first large-scale initiative bringing frontier AI models, massive compute, and frontier experimental capabilities under one roof. We're building a general-purpose system to accelerate scientific discovery, integrating frontier AI models, biological foundation models, and lab capabilities, with the ultimate goal of curing disease. Our technology powers scientists around the world, translating AI capabilities into tools that accelerate research everywhere.
 
 
 Biohub operates one of the largest AI compute clusters dedicated to biology, spanning three frontier research institutes with some of the world's leading biologists. We're not a startup trying to find product-market fit, and we're not a pharma company optimizing a pipeline. We're building frontier AI for fundamental science, as open science, at a scale no one else is doing. This is a unique moment for scientific acceleration. The problems are among the hardest and most impactful problems you can choose to work on, and we move at a pace that meets this moment.
 
 
 
 Our Research Spans
 
 
 
 <ul>
 <li>
 Frontier molecular modeling, from protein language models (e.g., ESM) to structure prediction (e.g., ESMFold) and beyond.
 </li>
 <li>
 Scaled biological foundation models trained on some of the largest GPU clusters dedicated to science
 </li>
 <li>
 Imaging foundation models trained across the world's largest microscopy datasets
 </li>
 <li>
 Reasoning and agentic systems that connect frontier LLMs with biological foundation models
 </li>
 <li>
 Mechanistic interpretability of biological foundation models: extracting new biological knowledge directly from model weights
 </li>
 <li>
 Scientific data at unprecedented scale: AI systems to collect, curate, and learn from some of the richest biological datasets ever assembled
 
 
 </li>
 </ul>
 Join our Team!
 
 
 As an ML Engineer, you'll join some of the strongest infrastructure engineers in AI, building the systems that connect everything together. The infrastructure problems you solve directly determine what science becomes possible.
 
 
 What You'll Do
 
 
 <ul>
 <li>
 Work with high-dimensional scientific data formats and contribute to backend compatibility, format evaluation, and I/O performance benchmarking at petabyte scale.
 </li>
 <li>
 Define and shape the engineering patterns your team and collaborating researchers will build on for years; the abstractions you write today become the foundation others depend on at scale.
 </li>
 <li>
 Work at the intersection of AI systems and biological discovery, where the infrastructure problems you solve directly determine what science becomes possible.
 </li>
 <li>
 Deploy models to production and manage artifact tracking across models and datasets.
 </li>
 <li>
 Design and optimize GPU-native data loading pipelines for large-scale multi-dimensional tensor workloads, including profiling and resolving hardware utilization bottlenecks across multi-backend systems.
 </li>
 <li>
 Work on simplification and improvement of codebase abstractions to accelerate research momentum.
 </li>
 <li>
 Build and maintain primitives for pre-training infrastructure that ensure the reliability and continuity of large-scale training runs.
 </li>
 <li>
 Help cultivate best practices in MLOps, and think about the full ML lifecycle, including data, fine-tuning, deployment, reliability and monitoring.
 </li>
 <li>
 Possesses the ability to execute complex modifications to the research pipeline, such as fast data loading and distributed training.
 </li>
 <li>
 Handle DevOps responsibilities, focused on making all engineers and researchers more productive. This includes tasks like cluster monitoring, unit testing and integration testing of research codebase, and continuous integration.
 </li>
 <li>
 Collaborate with partner researchers and engineers to deploy our technology within external infrastructure.
 
 
 </li>
 </ul>
 What You'll Bring
 
 
 <ul>
 <li>
 Hands-on experience with PyTorch, including custom training loops, distributed training, or low-level performance work.
 </li>
 <li>
 Familiarity with GPU-native data I/O tools and large-scale tensor formats (e.g. Zarr, HDF5, TensorStore, or similar).
 </li>
 <li>
 Experience with distributed computing frameworks such as Apache Spark, Dask, or Ray.
 </li>
 <li>
 Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
 </li>
 <li>
 Experience building or working with AI agent frameworks is a plus.
 </li>
 <li>
 A track record of building systems that other engineers and researchers depend on. Not just running experiments, but shipping infrastructure that scales.
 
 
 </li>
 </ul>
 
 Compensation
 
 
 
 The future anticipated Redwood City, CA, and New York City, NY base pay range for a role in this field is $150,000 to $350,000+ annually. Compensation ranges will vary based on job-related skills, level of experience, and knowledge. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.
 
 
 
 Benefits For The Whole You
 
 
 
 We&rsquo;re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible.
 
 
 <ul>
 <li>
 Provides a generous employer match on employee 401(k) contributions to support planning for the future.
 </li>
 <li>
 Paid time off to volunteer at an organization of your choice.
 </li>
 <li>
 Funding for select family-forming benefits.
 </li>
 <li>
 Relocation support for employees who need assistance moving
 
 
 </li>
 </ul>
 
 Please note that applying to this opportunity does not guarantee that we will be in touch with you regarding our opportunities. Our recruiting team will contact you if your experience aligns with the skills we seek for future open positions. We will keep your interest on file, contact you as opportunities arise, and send you information about the exciting work we are doing at Biohub. You can opt out at any time!
 
</div>

Machine Learning Engineer, AI

Mindrift

<div>
 
 Please submit your CV in English and indicate your level of English proficiency.
 
 
 
 Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems.
 
 Participation is project-based, not permanent employment.
 
 
 
 
 What This Opportunity Involves
 
 
 
 While each project involves unique tasks, contributors may:
 
 
 <ul>
 <li>
 Design original computational STEM problems that simulate real scientific workflows
 </li>
 <li>
 Create problems that require Python programming to solve
 </li>
 <li>
 Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks)
 </li>
 <li>
 Develop problems requiring non-trivial reasoning chains and creative problem-solving approaches
 </li>
 <li>
 Verify solutions using Python with standard libraries (Numpy, Pandas, Scipy, scikit-learn)
 </li>
 <li>
 Document problem statements clearly and provide verified correct answers
 
 
 </li>
 </ul>
 
 What We Look For
 
 
 
 This opportunity is a good fit for ML specialists with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:
 
 
 <ul>
 <li>
 5+ years of hands-on machine learning experience with proven business impact
 </li>
 <li>
 Portfolio of completed projects and publications showcasing real-world problem-solving
 </li>
 <li>
 Expert Python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels)
 </li>
 <li>
 Expert statistical analysis and machine learning - deep understanding of algorithms, methods, and their practical applications
 </li>
 <li>
 Expert with SQL and database operations for data manipulation and analysis
 </li>
 <li>
 Experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases)
 </li>
 <li>
 Understanding of MLOps practices and model deployment workflows
 </li>
 <li>
 Knowledge of modern frameworks (TensorFlow, PyTorch, LangChain)
 </li>
 <li>
 Strong written English (C1+)
 
 
 </li>
 </ul>
 
 How It Works
 
 
 
 Apply &rarr; Pass qualification(s) &rarr; Join a project &rarr; Complete tasks &rarr; Get paid
 
 
 
 Project time expectations
 
 
 
 For this project, tasks are estimated to require around 10-20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active.
 
 
 
 Compensation
 
 
 
 On this project, contributors can earn up to
 
 $90 per hour equivalent
 
 , depending on their level and pace of contribution.
 
 
 Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.
</div>

Freelance Machine Learning Engineer

<div>JOB DESCRIPTION 
Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As a Senior Lead Software Engineer - ML at at JPMorgan Chase within the Consumer &amp; Community Banking (CCB) line of business, you serve as a seasoned member of an agile team focused on building, scaling, and maintaining robust machine learning platforms. You will design and deliver trusted, market-leading infrastructure and tools that empower data scientists and ML engineers to develop, deploy, and monitor models efficiently and securely. You are responsible for implementing critical technology solutions across multiple technical areas to support the firm&rsquo;s business objectives and drive innovation in ML platform capabilities.
Job responsibilities<ul><li>
Design, build, and maintain scalable machine learning platforms and infrastructure to support end-to-end ML workflows.</li><li>
Develop and optimize tools for model training, deployment, monitoring, and lifecycle management.</li><li>
Integrate data engineering, feature management, and model serving capabilities into unified ML platform solutions.</li><li>
Implement secure, high-quality production code for platform services, APIs, and automation pipelines.</li><li>
Collaborate with data scientists, ML engineers, and product teams to understand requirements and deliver platform features that accelerate ML development and operations.</li><li>
Ensure platform reliability, scalability, and performance through proactive monitoring, troubleshooting, and continuous improvement.</li><li>
Produce architecture and design artifacts for platform components, ensuring alignment with enterprise standards and best practices.</li><li>
Automate infrastructure provisioning, configuration, and CI/CD pipelines for ML platform services.</li>
Contribute to the ML platform engineering community of practice and participate in events that explore new and emerging technologies. 
<li>
</li></ul>Required qualifications, capabilities, and skills<ul><li>
Formal training or certification on software engineering concepts and 5+ years applied experience</li><li>
Hands-on experience building, deploying, and maintaining machine learning platforms or infrastructure</li><li>
Proficiency in Python and one or more ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
</li><li>Experience with data processing frameworks and tools (e.g., Spark, Pandas, SQL)
</li><li>Practical experience with cloud-based ML platforms (e.g., AWS SageMaker, GCP AI Platform, Azure ML) or on-prem ML infrastructure</li><li>
Strong understanding of MLOps practices, including CI/CD for ML, model versioning, and monitoring</li><li>
Experience developing APIs and platform services for ML workflows
</li><li>Solid knowledge of the software development life cycle and agile methodologies
</li><li>Ability to collaborate with cross-functional teams to deliver platform solutions aligned with business objectives
</li></ul>Preferred qualifications, capabilities, and skills<ul><li>
Familiarity with Databricks for scalable data engineering and ML platform integration</li><li>
Experience working with Snowflake for cloud-based data warehousing and analytics</li><li>
Exposure to Snorkel AI for programmatic data labeling and training data management</li><li>
Experience with containerization and orchestration tools (e.g., Docker, Kubernetes, Airflow)</li><li>
Familiarity with feature stores, model registries, and ML metadata management</li><li>
Experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation)</li><li>
Experience with RESTful APIs and microservices architectures</li></ul>
ABOUT US 
Chase is a leading financial services firm, helping nearly half of America&rsquo;s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs.
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&rsquo; and employees&rsquo; religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
Equal Opportunity Employer/Disability/Veterans 
 
 
ABOUT THE TEAM 
 
Our Consumer &amp; Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We&rsquo;re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions &ndash; all while ranking first in customer satisfaction.</div>

Sr Lead Software Engineer - AI/ML

<div>JOB DESCRIPTION 
Be an integral part of an agile team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.
As an AWS Senior Lead Software Engineer- Java/Python at JPMorganChase within the Consumer and Community Bank- Connected Commerce Technology, you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Drive significant business impact through your capabilities and contributions, and apply deep technical expertise and problem-solving methodologies to tackle a diverse array of challenges that span multiple technologies and applications.
Job responsibilities<div>
</div><ul><li>Execute end-to-end software solutions &mdash; including design, development, and technical troubleshooting &mdash; with the ability to think beyond routine or conventional approaches to solve complex technical problems</li><li>
Develop secure, high-quality production code and maintain algorithms that run synchronously with appropriate systems</li><li>
Produce architecture and design artifacts for complex applications while ensuring design constraints are met throughout the software development process</li><li>
Gather, analyze, synthesize, and visualize data from large, diverse data sets to drive continuous improvement of software applications and systems</li><li>
Proactively identify hidden problems and patterns in data, leveraging these insights to drive improvements in coding hygiene and system architecture</li><li>
Contribute to software engineering communities of practice and events that explore new and emerging technologies</li><li>
Regularly provide technical guidance and direction to support the business and its technical teams, contractors, and vendors
</li><li>Drive decisions that influence the product design, application functionality, and technical operations and processes</li><li>
Serve as a function-wide subject matter expert in one or more areas of focus</li><li>
Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle</li><li>
Influence peers and project decision-makers to consider the use and application of leading-edge technologies
</li></ul>Required qualifications, capabilities, and skills<div>
</div><ul><li>Formal training or certification in software engineering concepts with 5+ years of applied experience</li><li>
Hands-on practical experience delivering system design, application development, testing, and operational stability</li><li>
Advanced proficiency in SQL and one or more programming languages including Java, springboot, microservices, or Python API development</li><li>
Strong experience designing and implementing solutions on AWS including hands-on experience with AWS infrastructure and services such as Step Functions, S3, SQS, Lambda, and AI/ML services such as SageMaker and Bedrock and AWS data processing and transformation services such as EMR, Glue, and Spark</li><li>
Experience working with data lake architectures and f
amiliarity with large-scale data platforms such as Snowflake and/or Databricks</li><li>
Exposure to AI/ML concepts, including model inference, evaluation, and deployment in production environments</li><li>
Proficiency in automation and continuous delivery methods</li><li>
Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)</li><li>
Ability to tackle design and functionality problems independently with little to no oversight
</li><li>Experience in Computer Science, Computer Engineering, Mathematics, or a related technical field</li></ul>
<div>Preferred qualifications, capabilities, and skills</div><div>
</div><ul><li>Experience building or integrating applications powered by large language models (LLMs), retrieval-augmented generation (RAG), or other generative AI techniques</li><li>
Familiarity with ML frameworks such as TensorFlow, PyTorch, or scikit-learn</li><li>
Experience with MLOps practices, including model versioning, monitoring, and automated retraining pipelines</li></ul>
ABOUT US 
<div>
<div>JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world&rsquo;s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
</div><div>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.
<div>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&rsquo; and employees&rsquo; 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 &amp; Co. is an Equal Opportunity Employer, including Disability/Veterans 
</div></div></div> 
 
ABOUT THE TEAM 
 
Our Consumer &amp; Community Banking Group depends on innovators like you to serve consumers, small businesses, municipalities and non-profits. You&rsquo;ll support the delivery of award winning tools and services that cover everything from personal and small business banking as well as lending, mortgages, credit cards, payments, auto finance and investment advice. This group is also focused on developing and delivering cutting edged mobile applications, digital experiences and next generation banking technology solutions to better serve our clients and customers.</div>

AWS Senior Lead Software Engineer- Java / Python

<div>JOB DESCRIPTION 
Join our global Quantitative Trading &amp; Research (QTR) team, where you'll apply your expertise in Derivatives Modelling, Financial Engineering, Data Science, and Quantitative Development. As part of JP Morgan's leading QTR Group, you'll innovate with unique analytics and mathematical models, enhancing business practices through automation. We develop advanced models and methodologies to support the Clearing business, utilizing the Athena quant platform for comprehensive trade and risk management across all asset classes.
Job summary:
As a Vice President Quantitative Researcher in the Quantitative Trading &amp; Research (QTR) Global Clearing team, you will lead the design, delivery, and governance of risk and pricing analytics and models across F&amp;O and OTC derivatives, with a primary focus on risk analytics, Initial Margin (IM) methodology, and production execution. You will set technical direction and partner closely with the Margin Trading desk, Technology, and Product Development to ship high-impact solutions. You will also shape our data-led strategy by applying state-of-the-art machine learning to transform risk management and automation across the investment bank.
Job responsibilities<ul><li>
Own delivery of front-office risk/pricing analytics and margin solutions using internal derivatives libraries, ensuring robust, performant outcomes across D1, F&amp;O, and OTC products; define multi-quarter roadmaps and drive continuous improvement.</li><li>
Lead end-to-end initiatives&mdash;from problem framing and hypothesis design through prototyping, backtesting, and scalable production deployment&mdash;partnering with Trading, QR peers, Technology, and Product to deliver measurable business impact.</li><li>
Design and enhance margin and derivative models, including methodology selection, calibration, numerical schemes, benchmarking/backtesting, documentation, and alignment with model risk governance.</li><li>
Serve as model owner: manage roadmaps, controls, monitoring/alerts, change management, and responses to Model Risk, Audit, and regulatory reviews; ensure explainability and transparency of assumptions, limitations, and model performance.</li><li>
Build and productionize analytics that advance intraday/EoD automation (services, APIs, pipelines) with clear SLOs/SLA, observability, reliability engineering practices, and tight integration into trading/risk platforms.</li><li>
Provide technical leadership and mentorship; conduct code/method reviews, establish research engineering best practices (testing, CI/CD, reproducibility), and develop team capability.</li><li>
Communicate complex quantitative concepts to non-technical audiences; influence product roadmaps, prioritization, and resourcing via data-driven analysis, scenario studies, and clear articulation of trade-offs.</li><li>
Lead development of ML/AI solutions end-to-end (feature engineering, model training/validation, MLOps, monitoring and drift management) with rigorous controls, documented governance, and demonstrable business value.</li><li>
Uphold standards for documentation, reproducibility, traceability, and SDLC; ensure compliance with internal policies for model risk management and data governance.</li></ul>
Required qualifications, capabilities, and skills<ul><li>
Advanced degree (PhD, MSc, or equivalent) in Mathematics, Physics, Statistics, Computer Science, or a related quantitative field.</li><li>
5+ years of front-office quant experience supporting trading/risk in F&amp;O and/or OTC derivatives, with a track record of production delivery and close trader partnership.</li><li>
Deep knowledge of listed and OTC derivatives; strong understanding of risk/P&amp;L attribution, sensitivities/Greeks, model assumptions/limitations, and market microstructure.</li><li>
Experience with front-office platforms such as SecDB, Athena, Quartz, or equivalent.</li><li>
Strong programming in Python and/or C++; experience architecting maintainable, testable, high-performance codebases and extending large-scale libraries; proficiency in numerical methods and performance tuning.</li><li>
Proven experience designing, calibrating, and maintaining IM/pricing models (e.g., curve construction, volatility surfaces, credit/rates models, margin frameworks), including performance monitoring and backtesting.</li><li>
Experience delivering production services with Technology partners (APIs, packaging, CI/CD, containerization, logging/monitoring); familiarity with data engineering and compute frameworks.</li><li>
Excellent quantitative problem-solving; able to decompose ambiguous problems, select appropriate methods, and communicate uncertainty and trade-offs clearly.</li><li>
Outstanding communication and stakeholder management; ability to influence across QR, Trading, Technology, and Product.</li><li>
Demonstrated mentorship or team leadership experience, including setting technical direction, conducting reviews, and managing priorities under pressure.</li></ul>
Preferred qualifications, capabilities, and skills<ul><li>
Expertise in curve building (multi-curve frameworks), volatility surface modeling/calibration (e.g., SABR, Heston, local/stochastic volatility), and numerical methods (PDE/FDM, Monte Carlo, adjoint/automatic differentiation).</li><li>
Experience with market risk, time-series/stress analytics, model risk governance, and regulatory expectations for pricing/risk models.</li><li>
Hands-on ML/AI for quant finance (signal extraction, surrogate modeling, anomaly detection), including MLOps, drift monitoring, and explainability.</li><li>
Knowledge of portfolio optimization, hedging algorithms, execution analytics, and transaction cost modeling.</li><li>
Familiarity with distributed computing and market data tooling (e.g., kdb+/q, SQL), and performance engineering for large-scale simulations.</li><li>
Contributions to research (internal notes, publications, patents, conference talks) and engagement with the open-source scientific computing ecosystem.</li></ul>
ABOUT US 
<div>
<div>JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world&rsquo;s most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
</div><div>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.
<div>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&rsquo; and employees&rsquo; 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 &amp; Co. is an Equal Opportunity Employer, including Disability/Veterans 
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ABOUT THE TEAM 
 
J.P. Morgan&rsquo;s Commercial &amp; Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial &amp; Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.</div>

Quantitative Trading & Research – Global Clearing – Vice President

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