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machine learning intern

Bloomberg

<div><div><div><div><div><div>Applied Machine Learning Engineer - Media Search and Recommendation
</div></div></div></div></div><div><div><div><div><div>Location
</div><div>New York
</div></div><div><div>Business Area
</div><div>Engineering and CTO
</div></div><div><div>Ref #
</div><div>10049313
</div></div></div></div></div><div><div><div><h2 class="jobSectionHeader"><b>Description &amp; Requirements
</b></h2></div></div><div><div><div><div><h3 class="jobSectionHeader">Our Team<b>
</b></h3>
<div>Bloomberg Media empowers global business leaders with breaking news, expert opinion and proprietary data distributed with global reach. With millions of unique visitors each month, our flagship website bloomberg.com is the go-to destination for those looking to stay ahead of the curve. As one of the top 10 most visited financial and news sites on the web, we take pride in delivering top-quality content that our audience can trust.</div>
<div>
The Search and Personalization team owns the core discovery experiences on Bloomberg.com and the Bloomberg mobile app. We are responsible for how users search for, discover, and engage with content across a global audience, with a strong focus on personalization and recommendations. By powering Bloomberg&rsquo;s discovery hub, we play a critical role in helping users find the content that matters most to them, ensuring experiences are relevant, timely, and high quality. Our systems operate at web scale and sit at the intersection of backend services, data pipelines, and user-facing experiences. We are looking for a dedicated and experienced Machine Learning engineer to join the team. The ideal candidate will have a passion for Machine Learning, building distributed web scale systems and partnering with a variety of stakeholders within our expansive organization.</div>
<h3 class="jobSectionHeader"><b>
</b>What's in it for you<b>
</b></h3>
<p>As a senior engineer on the Search and Personalization team, you will play a key role in expanding Bloomberg Media&rsquo;s investment in personalization. You&rsquo;ll work closely with product managers, data scientists, and machine learning engineers to design and build systems that power personalized discovery experiences for millions of users.</p>
<p>
You&rsquo;ll have ownership over impactful projects, from shaping technical direction to delivering production systems. The role offers a mix of backend, data, and potentially some frontend work, giving you the opportunity to influence the personalization models that deliver results to users. You&rsquo;ll be working on systems that are central to Bloomberg Media&rsquo;s growth and directly visible to a global audience.</p>
<h3 class="jobSectionHeader"><b>
</b><b>We&rsquo;ll trust you to</b><b>
</b></h3>
<ul><li> Lead the design and delivery of personalization and recommendation systems that power discovery across Bloomberg.com and mobile platforms.</li></ul>
<ul><li> Build and maintain data pipelines that support personalization, experimentation, and model-driven product experiences.</li></ul>
<ul><li> Design, develop, and evolve backend services and APIs that deliver personalized content at scale with low latency.</li></ul>
<ul><li> Partner closely with the data science team to productionize models and enable rapid experimentation.</li></ul>
<ul><li> Collaborate across the stack, including with frontend engineers, to deliver cohesive and high-quality user experiences.</li></ul>
<ul><li> Make architectural decisions, drive technical discussions, and help set technical direction for the personalization platform.</li></ul>
<ul><li> Mentor other engineers and raise the overall technical bar of the team.</li></ul><br>
<br>
<h3 class="jobSectionHeader"><b>You need to have</b><b>
</b></h3>
<ul><li> 5+ years of industry experience in an Object Oriented Programming language, preferably Python or Java</li></ul>
<ul><li> 5+ years of industry experience working with large data sets, performing machine learning model experimentation, implementation and deployment.</li></ul>
<ul><li> A Bachelor&rsquo;s degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent professional experience.</li></ul>
<h3 class="jobSectionHeader"><b>
</b><b>We&rsquo;d love to see</b><b>
</b></h3>
<ul><li> Exposure building and developing a content recommendation system, focusing on recommendation algorithms and machine learning capabilities</li></ul>
<ul><li> Familiarity building user behavioral models to predict users likelihood to perform high value actions like propensity to subscribe or churn</li></ul>
<ul><li> Experience with end-to-end machine learning projects, including data analysis, feature engineering, model selection, hyper-parameter tuning, model deployment and ongoing performance monitoring.</li></ul>
<h3 class="jobSectionHeader"><b>
</b><b>&middot;</b> <b>Hands-on expertise with big data systems and distributed data processing technologies such as Spark</b><b>
</b></h3><h3 class="jobSectionHeader"><b>&middot;</b> <b>Proven track record building and maintaining data pipelines that power customer-facing product features.</b><b>
</b></h3><h3 class="jobSectionHeader"><b>&middot;</b> <b>Demonstrated leadership delivering machine learning projects from inception through delivery.</b><b>
</b></h3><h3 class="jobSectionHeader"><b>&middot;</b> <b>Practical expertise with public cloud platforms such as AWS.</b><b>
</b></h3><h3 class="jobSectionHeader"><b>&middot;</b> <b>Proven ability to operate and evolve web-scale distributed systems in production.</b><b>
</b></h3>
</div></div><p></p><div><div><div>Salary Range = 165000 - 260000 USD Annually + Benefits + Bonus</div><div><br>
<div><br>
</div><div>The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.<div><br>
<br>
We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.<br>
</div></div></div></div></div><div><div>Discover what makes Bloomberg unique - watch our for an inside look at our culture, values, and the people behind our success.</div></div></div></div></div></div>

Applied Machine Learning Engineer - Media Search and Recommendation

Point72

<div><div><div><p><b>EXPERIENCE</b></p>
<div>Experienced Professionals</div>
</div><div><p><b>LOCATION</b></p>
<div>New York</div>
</div><div><p><b>FOCUS</b></p>
<div>Software &amp; System Engineering</div>
</div><div><p><b>BUSINESS</b></p>
<div>Point72</div></div></div></div>
<br><div><h3 class="jobSectionHeader"><b>A Career with Point72&rsquo;s Knowledge Graph Intelligence Team</b></h3>
<p>
On the Knowledge Graph Intelligence team, you&rsquo;ll work alongside product managers, engineers, and data scientists to build the next generation of intelligent systems through graph technology. We&rsquo;re a team of experts who experiment and work to discover new ways to harness open-source solutions, modern cloud architectures, and sophisticated Artificial Intelligence (AI) solutions, while embracing enterprise agile methodologies. Our commitment to building and innovating in the AI space provides the framework intended to drive smarter decision-making and enhance how we build and operate our platforms and applications.</p><h3 class="jobSectionHeader"><b><br>
What you&rsquo;ll do</b></h3>
<p>
In this data-heavy role, you will design and build mission-critical infrastructure that powers our machine learning lifecycle, from large-scale data processing and feature engineering to model training, real-time deployment, and monitoring. Specifically, you will:</p><br>
<p></p><ul><li>
Architect and implement the full lifecycle of ML models, from data ingestion to production inference, contributing to the design of our next-generation, event-driven architecture, using technologies like gRPC, Kafka, and high-performance API frameworks, like FastAPI, Spring WebFlux, and Axum.</li><li>
Engineer and automate robust, large-scale data processing pipelines (ETL/ELT) using tools like Spark, dbt, and workflow orchestrators, and lead the design and implementation of our Feature Store strategy.</li><li>
Own the MLOps framework for model training, versioning, and deployment, including CI/CD pipelines, automated workflows, and experiment tracking and evaluation tooling.</li><li>
Implement sophisticated deployment strategies, including canary, blue-green, shadow, and A/B testing, to ensure safe, zero-downtime releases, and optimize inference performance for LLMs and other large models.</li><li>
Leverage cutting-edge tools and techniques like quantization and compilation to maximize throughput and minimize latency.</li><li>
Collaborate with data scientists to develop models and optimize model performance for low-latency serving using techniques like Python performance tuning.</li><li>
Define, provision, and manage our cloud infrastructure using Terraform, working hands-on with a wide array of cloud services across compute, storage, and machine learning platforms.</li></ul><br>
<h3 class="jobSectionHeader"><b>
What&rsquo;s required</b></h3>
<ul><li>5+ years of experience in a software, data, or ML engineering role.</li><li>
Strong proficiency in SQL.</li><li>
Experience building and orchestrating data pipelines using tools such as Spark, dbt, and Dagster/Airflow, as well as data warehouses like Snowflake, Redshift, BigQuery.</li><li>
Understanding of infrastructure as code, including experience with Terraform.</li><li>
Proficiency with containerization and orchestration including Docker and Kubernetes.</li><li>
Hands-on experience with CI/CD tools and ML lifecycle tools, including Jenkins, MLflow, Kubeflow, and W&amp;B.</li><li>
Experience with AWS and its core services including S3, EC2, Lambda, RDS, and EMR, and practical experience with Boto3 and AWS ML services SageMaker and Bedrock.</li><li>
Understanding of modern ML models and ability to discuss the performance characteristics and engineering trade-offs that influence deployment decisions.</li><li>
Experience with systems incorporating Graph Neural Networks (GNNs), recommendation systems, anomaly detection, and complex time-series models.</li><li>
Commitment to the highest ethical standards.</li></ul><br>
<h3 class="jobSectionHeader"><b>
We take care of our people</b></h3>
<p>
We invest in our people, their careers, their health, and their well-being. When you work here, we provide:</p>
<ul><li>
Fully-paid health care benefits</li><li>
Generous parental and family leave policies</li><li>
Mental and physical wellness programs</li><li>
Volunteer opportunities</li><li>
Non-profit matching gift program</li><li>
Support for employee-led affinity groups representing women, minorities and the LGBT+ community</li><li>
Tuition assistance</li><li>
A 401(k) savings program with an employer match and more</li></ul><br>
<h3 class="jobSectionHeader"><b>
About Point72</b></h3>
<p>
Point72 Asset Management is a global firm led by Steven Cohen that invests in multiple asset classes and strategies worldwide. Resting on more than a quarter-century of investing experience, we seek to be the industry&rsquo;s premier asset manager through delivering superior risk-adjusted returns, adhering to the highest ethical standards, and offering the greatest opportunities to the industry&rsquo;s brightest talent. We&rsquo;re inventing the future of finance by revolutionizing how we develop our people and how we use data to shape our thinking. For more information, visit <b>www.Point72.com/working-here</b></p><p><br>
The annual base salary range for this role is $175,000-$250,000 (USD) , which does not include discretionary bonus compensation or our comprehensive benefits package. Actual compensation offered to the successful candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level, among other things.</p></div>

Software Engineer, Machine Learning

Middesk

<div>
 <strong>
  About Middesk
  <br/>
  <br/>
 </strong>
 Middesk makes it easier for businesses to work together. Since 2018, we&rsquo;ve been transforming business identity verification, replacing slow, manual processes with seamless access to complete, up-to-date data. Our platform helps companies across industries confidently verify business identities, onboard customers faster, and reduce risk at every stage of the customer lifecycle.
 <br/>
 <br/>
 Middesk came out of Y Combinator, is backed by Sequoia Capital and Accel Partners, and was recently named to Forbes Fintech 50 List.
 <br/>
 <br/>
 <strong>
  The Role:
  <br/>
  <br/>
 </strong>
 We&rsquo;re building AI-driven applications that power business onboarding, fraud prevention, and identity verification. With proprietary data assets and deep domain expertise, we&rsquo;re uniquely positioned to create a new generation of ML-powered solutions for trust and risk.
 <br/>
 <br/>
 We&rsquo;re looking for a
 <strong>
  hands-on Machine Learning Engineer with strong Data Science expertise
 </strong>
 to take end-to-end ownership of the ML lifecycle: from feature design and model development, to deployment, monitoring, and iteration in production. Unlike larger organizations where responsibilities are split, you&rsquo;ll have the opportunity to
 <strong>
  own models from concept to production
 </strong>
 while working closely with product managers, engineers, and data platform teammates who support and amplify your work.
 <br/>
 <br/>
 This is a rare chance to join an
 <strong>
  earlier-stage company
 </strong>
 where you&rsquo;ll have broad visibility and influence, and where your ML systems will have immediate and measurable impact on customers.
 <br/>
 <br/>
 What You&rsquo;ll Do:
 <br/>
 <br/>
 <ul>
  <li>
   End-to-end ML ownership: Lead the full lifecycle of ML systems &mdash; feature engineering, model design, training, evaluation, deployment, monitoring, and iteration.
  </li>
  <li>
   Collaborate with a strong team: Work alongside data engineers, platform engineers, and product teammates who ensure you have the infrastructure, data, and context to deliver.
  </li>
  <li>
   Design &amp; deploy production models: Build high-performance ML applications in risk, fraud, trust &amp; safety, and compliance domains.
  </li>
  <li>
   Keep models healthy in production: Proactively monitor, detect drift, and retrain to ensure long-term performance and reliability.
  </li>
  <li>
   Experiment &amp; learn: Drive online experiments, offline evaluation, and counterfactual analyses to prove impact.
  </li>
  <li>
   Shape ML foundations: Contribute to the feature store, model management, training/serving pipelines, and best practices that scale ML across multiple use cases.
   <br/>
   <br/>
  </li>
 </ul>
 What We&rsquo;re Looking For:
 <br/>
 <br/>
 <ul>
  <li>
   4+ years applied ML experience with proven impact in risk, fraud, trust &amp; safety, compliance, fintech, or other high-stakes domains.
  </li>
  <li>
   Track record of owning ML models end-to-end &mdash; from research and design to deployment, monitoring, and retraining in production.
  </li>
  <li>
   Strong software engineering skills (Python, ML frameworks, deployment pipelines) and ability to write reliable, production-grade code.
  </li>
  <li>
   Hands-on experience with ML infrastructure such as feature stores, model management, training/serving pipelines, and monitoring tools.
  </li>
  <li>
   Comfortable as a senior IC: you can set technical direction, establish best practices, and mentor peers while collaborating effectively across teams.
  </li>
  <li>
   Experience working cross-functionally with data engineers, platform engineers, and product stakeholders to bring ML systems to life.
  </li>
  <li>
   Deep expertise in classification challenges such as imbalanced labels, sparse signals, cold start, and production version management.
   <br/>
   <br/>
  </li>
 </ul>
 Nice to Haves:
 <br/>
 <br/>
 <ul>
  <li>
   B2B SaaS experience, ideally building ML products for enterprise customers.
  </li>
  <li>
   Familiarity with graph, LLM-based feature generation, or AI agent workflows.
  </li>
  <li>
   Experience scaling ML across multiple products or risk domains.
  </li>
 </ul>
</div>


Machine Learning Engineer

Warner Bros. Discovery

<div><p><b><i>Welcome to Warner Bros. Discovery&hellip; the stuff dreams are made of.</i></b></p><p></p><p><b>
Who We Are&hellip;
</b></p><p>When we say, &ldquo;the stuff dreams are made of,&rdquo; we&rsquo;re not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD&rsquo;s vast portfolio of iconic content and beloved brands, are the <i>storytellers</i> bringing our characters to life, the<i> creators</i> bringing them to your living rooms and the <i>dreamers</i> creating what&rsquo;s next&hellip;</p><p></p><p>
From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive.</p><p></p><p>
We are the now and the next. The power behind the people building the future. We are born from the spirit of innovation. We are created from the idea that people around the world want more, need more, deserve more. We are the home of the global digital revolution. We are CNN.</p><p></p><p>
To see what it&rsquo;s like to work at CNN, follow @WBDLife on Instagram and X!</p><p></p><p>
TA WILL POST.</p><p></p><p><b>
How We Get Things Done&hellip;</b></p><p></p><p>
This last bit is probably the most important! Here at WBD, our guiding principles are the core values by which we operate and are central to how we get things done. You can find them at www.wbd.com/guiding-principles/ along with some insights from the team on what they mean and how they show up in their day to day. We hope they resonate with you and look forward to discussing them during your interview.</p><p></p><p><b>
Championing Inclusion at WBD</b></p>
Warner Bros. Discovery embraces the opportunity to build a workforce that reflects a wide array of perspectives, backgrounds and experiences. Being an equal opportunity employer means that we take seriously our responsibility to consider qualified candidates on the basis of merit, without regard to race, color, religion, national origin, gender, sexual orientation, gender identity or expression, age, mental or physical disability, and genetic information, marital status, citizenship status, military status, protected veteran status or any other category protected by law.<p></p><p>
If you&rsquo;re a qualified candidate with a disability and you require adjustments or accommodations during the job application and/or recruitment process, please visit our accessibility page for instructions to submit your request.</p><p></p>
In compliance with local law, we are disclosing the compensation, or a range thereof, for roles in locations where legally required. Actual salaries will vary based on several factors, including but not limited to external market data, internal equity, location, skill set, experience, and/or performance. Base pay is just one component of Warner Bros. Discovery&rsquo;s total compensation package for employees. Pay Range: $99,400.00 - $184,600.00 salary per year. Other rewards may include annual bonuses, short- and long-term incentives, and program-specific awards. In addition, Warner Bros. Discovery provides a variety of benefits to employees, including health insurance coverage, an employee wellness program, life and disability insurance, a retirement savings plan, paid holidays and sick time and vacation.</div><p></p>

Machine Learning Engineer I

mecka

<div><h2 class="jobSectionHeader"><b>The Role</b></h2><p>
We're hiring an <b>ML and Optimization Specialist</b> to lead model architecture improvements across all of Mecka's pipelines.</p><p>
This role is heavily focused on foundational deep learning engineering rather than applied ML. We are looking for an engineer who natively writes, debugs, and modifies internal model architectures from the ground up, moving beyond utilizing off-the-shelf models or standard fine-tuning.</p><p>
Many of our current ML systems rely heavily on <b>frame-by-frame models</b>, but all of our data is inherently temporal. Your immediate focus will be <b>converting and optimizing these models for temporal inference</b> &mdash; a critical unlock for pipeline performance.</p><p>
Beyond that, you'll be the go-to person for <b>model-level debugging, architecture design, and optimization</b> across the organization. This is a high-leverage, deeply technical role for someone who thinks at the architecture level.</p><h2 class="jobSectionHeader"><b>
Responsibilities</b></h2><h3 class="jobSectionHeader"><b>
Immediate Priorities</b></h3><ul><li><p><b>
Temporal model conversion</b> &mdash; migrate frame-by-frame models to temporal architectures that leverage sequential data</p></li><li><p>
Benchmark and validate temporal models against existing frame-based baselines</p></li></ul><h3 class="jobSectionHeader"><b>
Ongoing</b></h3><ul><li><p>
Lead <b>model architecture improvements</b> across all pipelines (CV, pose estimation, etc.)</p></li><li><p>
Tune and debug ML models at the <b>model architecture level</b> &mdash; modifying structural code, writing custom layers, and addressing the underlying math, rather than relying solely on high-level APIs or hyperparameter tuning</p></li><li><p>
Profile and optimize model performance (latency, throughput, memory)</p></li><li><p>
Evaluate and introduce new architectures, training strategies, and optimization techniques</p></li><li><p>
Collaborate with CV, ML, and infrastructure teams to deploy improved models</p></li></ul><h2 class="jobSectionHeader"><b>
Who You Are</b></h2><h3 class="jobSectionHeader"><b>
Required Skills</b></h3><ul><li><p>
Deep expertise in <b>ML model architecture design and optimization</b></p></li><li><p>
Ability to <b>tune and debug models at the architecture level</b> &mdash; diagnosing issues in attention mechanisms, loss landscapes, gradient flow, etc.</p></li><li><p>
Strong experience with <b>temporal/sequential models</b> (transformers, RNNs, temporal convolutions, state-space models)</p></li><li><p>
Proficiency in <b>PyTorch</b> (or equivalent) at a research-engineering level</p></li><li><p>
Experience optimizing models for production deployment</p></li></ul><h3 class="jobSectionHeader"><b>
Strong Signals</b></h3><ul><li><p>
Published papers or production experience with video understanding or temporal perception</p></li><li><p>
Experience with model distillation, quantization, or efficient inference</p></li><li><p>
Background in computer vision model architectures</p></li><li><p>
Experience converting or adapting pre-trained models to new domains/modalities</p></li><li><p>
Familiarity with ONNX, TensorRT, or similar inference optimization tools</p></li></ul><h3 class="jobSectionHeader"><b>
You Are</b></h3><ul><li><p>
Obsessed with model internals &mdash; you think in terms of structural architecture and custom implementations, rather than just training runs and applied endpoints</p></li><li><p>
Able to move between research papers and production code</p></li><li><p>
A strong communicator who can explain architecture tradeoffs to cross-functional teams</p></li></ul><h2 class="jobSectionHeader"><b>
Why This Role</b></h2><ul><li><p>
Own the model architecture strategy across all of Mecka's pipelines</p></li><li><p>
Solve a critical temporal modeling challenge with immediate impact</p></li><li><p>
Work at the intersection of perception, robotics, and ML systems</p></li><li><p>
High ownership in a fast-moving, well-funded robotics AI company</p></li></ul><p>
Compensation Range: $160K - $250K</p></div>

Core ML Engineer: Deep Learning Architecture

JPMorganChase

<div><b>JOB DESCRIPTION</b><p><br>
The Chief Data &amp; Analytics Office (CDAO) at JPMorgan Chase is responsible for accelerating the firm&rsquo;s data and analytics journey. This includes ensuring the quality, integrity, and security of the company's data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm&rsquo;s commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management effectively and responsibly.</p><p>
This role offers the unique opportunity to explore novel and complex challenges that could profoundly transform how the bank operates.
</p><p>As a Machine Learning Director, you will have the opportunity to apply sophisticated machine learning methods to complex tasks including natural language processing, speech analytics, time series, reinforcement learning and recommendation systems. You will collaborate with various teams and actively participate in our knowledge sharing community. We are looking for someone who excels in a highly collaborative environment, working together with our business, technologists and control partners to deploy solutions into production. If you have a strong passion for machine learning and enjoy investing time towards learning, researching and experimenting with new innovations in the field, this role is for you. We value solid expertise in Deep Learning with hands-on implementation experience, strong analytical thinking, a deep desire to learn and high motivation.</p><p>
Job Responsibilities</p><ul><li>
Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community</li><li>
Develop state-of-the art machine learning models to solve real-world problems and apply it to tasks such as natural language processing (NLP), speech recognition and analytics, time-series predictions or recommendation systems</li><li>
Collaborate with multiple partner teams such as Business, Technology, Product Management, Legal, Compliance, Strategy and Business Management to deploy solutions into production</li>
Drive Firm wide initiatives by developing large-scale frameworks to accelerate the application of machine learning models across different areas of the business<br>
<li>
</li></ul><p>Required qualifications, capabilities, and skills</p><ul><li>
PhD in a quantitative discipline, e.g. Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science Or an MS with at least 7 years of industry or research experience in the field.</li><li>
Solid background in NLP or speech recognition and analytics, personalization/recommendation and hands-on experience and solid understanding of machine learning and deep learning methods</li><li>
Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)</li><li>
Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals</li><li>
Experience with big data and scalable model training and solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences.</li><li>
Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments</li><li>
Solid written and spoken communication to effectively communicate technical concepts and results to both technical and business audiences. Curious, hardworking and detail-oriented, and motivated by complex analytical problems</li></ul><p>
Preferred qualifications, capabilities , and skills:</p><ul><li>
Strong background in Mathematics and Statistics and familiarity with the financial services industries and continuous integration models and unit test development</li><li>
Knowledge in search/ranking, Reinforcement Learning or Meta Learning</li><li>
Experience with A/B experimentation and data/metric-driven product development, cloud-native deployment in a large scale distributed environment and ability to develop and debug production-quality code</li><li>
Published research in areas of Machine Learning, Deep Learning or Reinforcement Learning at a major conference or journal</li></ul><p>
</p><p><b>#MLCOE_jobs</b></p>
<b>ABOUT US</b><br>
<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><p></p><div><p>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.
</p><div><p>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.</p>
<p>JPMorgan Chase &amp; Co. is an Equal Opportunity Employer, including Disability/Veterans</p><br>
</div></div></div><br>
<br>
<b>ABOUT THE TEAM</b><br>
<br>
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&rsquo;re setting our businesses, clients, customers and employees up for success.</div>

Applied AI ML Director Machine Learning Center of Excellence

Fendi

<div>
 <strong>
  Position
  <br/>
  <br/>
 </strong>
 Intern, Supply Chain
 <br/>
 <br/>
 <strong>
  Overview
  <br/>
  <br/>
 </strong>
 Job responsibilities:
 <br/>
 <br/>
 The Supply Chain Planning Intern will assist the Senior Manager, Planning, in helping the demand and distribution team to react fast to the daily challenges of a supply chain environment. The intern will assist the Senior Manager, Planning, in managing stock allocation and identifying opportunities to improve sales performance and product categories by market for FENDI Americas to identify opportunities and drive business.
 <br/>
 <br/>
 <strong>
  FENDI is committed to ensuring that its Internship Program provides a robust experience with a combination of learning and programmatic elements.
  <br/>
  <br/>
 </strong>
 <strong>
  Responsibilities
  <br/>
  <br/>
 </strong>
 <ul>
  <li>
   Support the daily Supply Chain activities around stock management: distribution planning, stock rebalancing and sell-through optimization.
  </li>
  <li>
   Support in reviewing historical sales trends, research demand drivers, prepare forecast data, develop statistical forecast models, and evaluate forecast results
  </li>
  <li>
   Support closely with the coordination and communication with planning and logistics team to secure additional inventory when demand exceeds the forecast; Experience in sales forecasting.
  </li>
  <li>
   Support the Senior Manager, Planning in optimizing sales and sell through for seasonal product by creating tools to analyze datasets in a centralized platform/dashboard.
  </li>
  <li>
   Support the Senior Manager, Planning in preparing presentations for senior leaders and business reviews
  </li>
  <li>
   Support in the allocation of merchandise to stores and E-Commerce according to launch plan, warehouse and store inventory levels.
  </li>
  <li>
   Run stock reports to ensure the visibility of deliveries. Build alerts to minimize the &ldquo;sleeping&rdquo; inventory and ensure a follow up to increase our deliveries rate in the season
  </li>
  <li>
   Support in coordinating merchandise transfers to fulfill stock needs, refresh assortments and support events (i.e. caravans and trunk shows)
  </li>
  <li>
   Development of reporting dashboard for Planning and Management team, using Microsoft Power BI
  </li>
  <li>
   Support store openings / closing plans
   <br/>
   <br/>
  </li>
 </ul>
 <strong>
  Qualifications
  <br/>
  <br/>
 </strong>
 Additional information:
 <br/>
 <br/>
 <ul>
  <li>
   Must be available to work Monday-Friday: 9-6pm
  </li>
  <li>
   Bachelor&rsquo;s degree or previous internship experience in a related field preferred
  </li>
  <li>
   Proficiency in Microsoft Excel, PowerPoint, and Word.
  </li>
  <li>
   Advanced knowledge of Power BI. SQL, and/or Python.
  </li>
  <li>
   Excellent communications skills.
  </li>
  <li>
   Highly organized with a strong attention to detail.
  </li>
  <li>
   Must be self-motivated and work autonomously.
  </li>
  <li>
   Passion for Fendi and the Luxury Industry
  </li>
 </ul>
</div>


Intern, Supply Chain

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