Search jobs > Seattle, WA > Machine learning engineer

Machine Learning Engineer, Payments ML Accelerator

Stripe
Seattle
$192K-$288K a year
Full-time

Who we are

About Stripe

Stripe is a financial infrastructure platform for businesses. Millions of companies from the world’s largest enterprises to the most ambitious startups use Stripe to accept payments, grow their revenue, and accelerate new business opportunities.

Our mission is to increase the GDP of the internet, and we have a staggering amount of work ahead. That means you have an unprecedented opportunity to put the global economy within everyone’s reach while doing the most important work of your career.

About the team

The Payments ML Accelerator team is developing capabilities that will unlock the proliferation of ML based techniques across Stripe’s payment products.

We are developing cutting edge deep learning models tailored to Stripe’s payment data, and infrastructure to enable rapid ML exploration and very fast experiment cycles.

We are exploring novel applications powered by ML as well as improving core product features such as detecting fraudulent transactions across all payment methods or optimizing payment acceptance rate.

What you’ll do

As a machine learning engineer, you will design and build platforms and services that are configurable and scalable. You will have the opportunity to build and deploy advanced ML applications and generalizable feature engineering pipelines, with the aim to produce business impact and raise the bar for technical excellence.

You will also have the opportunity to contribute to and influence ML architecture at Stripe.

Responsibilities

  • Build and deploy deep learning architectures and feature embeddings for Payment entities such as merchant, issuer, or customer
  • Develop DNN applications and establish the foundation to facilitate increased DNN adoption at Stripe
  • Design and architect generalizable ML workflows for rapid expansion of existing ML solutions
  • Experiment with advanced ML solutions in the industry and ideate on product applications
  • Collaborate with our machine learning infrastructure team to leverage new infra services for business solutions
  • Collaborate with data scientists to build ML models

Who you are

We are looking for ML Engineers who are passionate about using ML to improve products and delight customers. You have experience developing streaming feature pipelines, building ML models, and deploying them to production, even if it involves making substantial changes to backend code.

You are comfortable with ambiguity, love to take initiative, and have a bias towards action.

Minimum requirements

  • At least 5 years of industry experience doing end-to-end ML development on a machine learning team and bringing ML models to production
  • Advanced degree in a quantitative field (e.g. computer science, statistics, physics, )
  • Proficient in Python, Scala, Spark

Preferred qualifications

  • Knowledge about how to manipulate data to perform analysis, including querying data, defining metrics, or slicing and dicing data to evaluate a hypothesis.
  • Experience evaluating niche and upcoming ML solutions

Hybrid work at Stripe

This role is available either in an office or a remote location (typically, 35+ miles or 56+ km from a Stripe office).

Office-assigned Stripes spend at least 50% of the time in a given month in their local office or with users. This hits a balance between bringing people together for in-person collaboration and learning from each other, while supporting flexibility about how to do this in a way that makes sense for individuals and their teams.

A remote location, in most cases, is defined as being 35 miles (56 kilometers) or more from one of our offices. While you would be welcome to come into the office for team / business meetings, on-sites, meet-ups, and events, our expectation is you would regularly work from home rather than a Stripe office.

Stripe does not cover the cost of relocating to a remote location. We encourage you to apply for roles that match the location where you currently or plan to live.

Pay and benefits

The annual US base salary range for this role is $192,000 - $288,000. For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions / sales bonuses target and annual base salary for the role.

This salary range may be inclusive of several career levels at Stripe and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, and location.

Applicants interested in this role and who are not located in the US may request the annual salary range for their location during the interview process.

Additional benefits for this role may include : equity, company bonus or sales commissions / bonuses; 401(k) plan; medical, dental, and vision benefits; and wellness stipends.

30+ days ago
Related jobs
Promoted
Apple Inc.
Seattle, Washington

We are looking for engineers who are passionate about building systems that push the frontier of deep learning in terms of scaling, efficiency, and flexibility and delight millions of users in Apple products. Extensive experience in applied machine learning, modeling, and productization. Experience ...

Promoted
VirtualVocations
Seattle, Washington

A company is looking for a Customer Support Engineer, Machine Learning based in the US (Remote). Key Responsibilities:Quickly respond to all inbound support requests including email, live chat and community forumsTriage bugs and requests based on customer type and severity of issueMaintain a fast re...

Promoted
TikTok
Seattle, Washington

We use state-of-the-art large-scale machine learning technology, the cutting-edge NLP, CV and multi-modal technology to build the industry's top-class search engine to provide the best e-commerce search experience, for more than 1 billion monthly active TikTok users around the world. ...

Promoted
Snap Inc
Seattle, Washington

We're looking for a Staff Machine Learning Engineer to join Snap Inc!. Experience working with machine learning frameworks such as TensorFlow, Caffe2, PyTorch, Spark ML, scikit-learn, or related frameworks. Strong understanding of machine learning approaches and algorithms. Experience working with m...

Promoted
TikTok
Seattle, Washington

We are seeking brilliant and motivated graduate software engineers, who are eager to apply their knowledge in machine learning (ML), operations research (OR), data mining, and statistical inference to real-world challenges. Strong understanding of applied machine learning and Big Data tools. Contrib...

Promoted
TikTok
Seattle, Washington

As a Machine Learning Engineer on the App Ads & Gaming team, you will make efforts to develop novel machine learning solutions for ranking, build scalable foundations and launch various products that maximize the efficiency of deep funnel app ads delivery. Hence, you'll have a chance to get deep...

Promoted
TikTok
Seattle, Washington

Familiar with federated learning / distributed machine learning algorithms and experienced in federated learning frameworks and applications development. Interest in privacy-enhanced techniques (PET) and related technical domains, including data and identity anonymization, differential privacy, secu...

Stripe
Seattle, Washington

As a machine learning engineer, you will be responsible for analyzing opportunities, proposing ideas, training & evaluating ML models, running experiments, and deploying everything to production. At least 5 years of industry experience doing end-to-end ML development on a machine learning team and b...

TikTok
Seattle, Washington

Participate in the development and iteration of Ads algorithms by using Machine Learning, including ads query understanding, ads targeting, ads ranking, model serving reliability, etc. Good theoretical grounding in the machine and deep learning concepts and techniques (CNN/RNN/LSTM,. Familiar with t...

ByteDance
Seattle, Washington

Hands-on experience with data structure algorithms, machine learning models such as sales forecasting, classification task, deep learning etc. Responsibilities:- Improve the working efficiency of e-commerce merchants, influencers, and account managers to boost the growth of sellers' products, custom...