About Us

Riskified empowers merchants and shoppers to realize the full potential of eCommerce by making it safe, accessible, and frictionless. Our global team helps the world’s most-innovative eCommerce merchants eliminate risk and uncertainty from their business. Merchants integrate Riskified’s machine learning platform to create trusted customer relationships, driving higher sales while reducing costs. Riskified has reviewed hundreds of millions of transactions and approved billions of dollars of revenue for global brands and fast-growing businesses across industries, including Wayfair, Wish, Peloton, Gucci, and many more. As of July 29th, 2021, Riskified has begun trading on NYSE under the ticker RSKD. Check out the Riskified Technology Blog for a deeper dive into our R&D work.

Our Research Team

• We are focused on bringing value to Riskified through the development of models and analytical solutions across domains. We use a wide variety of advanced techniques and algorithms to provide maximum value from data in all shapes and sizes: classic ML and deep learning, supervised and unsupervised, NLP, anomaly detection, graph theory, and more.
• We use the most cutting-edge solutions - from event driven (Kafka), to big data solutions (Spark), Cloud operations (Docker & Kubernetes), Workflow orchestration (Airflow & Argo) and Machine Learning Platforms (Databricks & Kubeflow), working mostly in Python, Scala and R.
• We’re a friendly, fun and diverse team. We’re passionate about making data-driven decisions, being open-minded and creative, while communicating openly and honestly. We thrive in a continuous learning culture to promote growth and remain at the forefront of technological innovation.
  
  

About The Role

In this role, you'll merge data science expertise with MLOps proficiency, developing and implementing advanced analytical solutions for real-world applications. Your primary focus will be on constructing the infrastructure necessary for the computational aspects of training machine learning models. Through collaboration with cross-functional teams, you'll integrate these ML capabilities seamlessly into our product ecosystem, driving efficient, data-driven outcomes.

What You'll Be Doing

• Developing Advanced Analytical Solutions: You will be instrumental in designing and implementing production-grade analytical tools and systems. Your work will involve transforming complex data science concepts into practical, scalable solutions that drive real-world results.
• Building Autonomous ML Platforms: A significant part of your role will be focused on maintaining, improving and delivering a robust software platform. This platform will autonomously train and deploy machine learning models, significantly enhancing our ability to respond to data-driven challenges swiftly and effectively. Ideal candidates are those who possess a deep understanding of both data science practices/ flows and the infrastructure that supports it.
• Facilitating Data Science Excellence through MLOps Frameworks: In this vital role, your primary objective is to gain a deep understanding of the needs and challenges faced by our Data Science team. Utilising this insight, you will build or leverage existing MLOps solutions to maximise our business impact. This involves bridging the gap between Data Science and Business Objectives, implementing scalable MLOps frameworks, adopting an example-driven approach, enhancing Data Science productivity, and fostering collaborative innovation.
  
  

Qualifications

• Strong programming skills in languages such as Python and Scala.
• MSc in Statistics, Computer Science, Mathematics, or a related field.
• Minimum of 3 years of experience as a Machine Learning Engineer or a similar role, with a consistent record of successfully delivering ML solutions.
• Proficiency in engines for extensive data processing (e.g., Spark, Scala, Kafka).
• Resilient ETL processes, and vigilance over data integrity in cloud environments.
• Experience with large-scale database systems (e.g. Elasticsearch, Snowflake).
• Proven familiarity with working within public cloud environments (e.g., AWS)
• Experience with cloud frameworks like AWS sagemaker and training models using TensorFlow, PyTorch, or scikit-learn.
• Demonstrated experience in the application of MLOps tools, such as mlflow, Weights & Biases, CI/CD frameworks and Airflow, along with expertise in the utilisation of serving platforms and feature stores, contributing to enhanced operational efficiency in machine learning processes.
  
  

Advantages

• Familiarity with Large Language Model (LLM) frameworks.
• Prior experience in working as a software engineer in collaboration with Data Scientists, Algorithm Developers, and Researchers.
  
  

If you are a passionate ML Engineer with a strong background in machine learning and a desire to make a significant impact with your analytical skills, we would love to hear from you. Join our team and be a part of driving data-driven decision-making at Riskified.

Life at Riskified

We are a fast-growing and dynamic tech company with 750+ team members globally. We value collaboration and innovative thinking. We’re looking for bright, driven, and passionate people to grow with us.

Our Tel-Aviv team is currently working in a hybrid of remote and in-office work for all our team members. We have recently moved to our new space in Tel Aviv - check it out here!

Some Of Our Tel Aviv Benefits & Perks

• Equity for all employees, Keren Hishtalmut, pension
• Private medical insurance, extra time off for parents and caregivers
• Commuter and parking benefits
• Team events, fully-stocked kitchen, lunch stipend, happy hours, yoga, pilates, functional training, basketball, soccer
• Wide-ranging opportunities to volunteer and make an impact
• Commitment to your professional development with global onboarding, skills-based courses, full access to Udemy, lunch & learns
• Awesome Riskified gifts and swag!
  
  

Riskified is deeply committed to the principle of equal opportunity for all individuals. We do not discriminate based on race, color, religion, sex, sexual orientation, national origin, age, disability, veteran status, or any other status protected by law.