Senior Software Engineer, ML Engineering

Who Are You

We seek a skilled and highly motivated Senior Software Engineer to join our dynamic and growing ML Engineering team. As a Senior Software Engineer for ML Engineering, you will be part of the team that builds platforms that empower fellow engineers and Data Scientists to create market-leading fraud prevention products. We want you to help us scale our business, make data-driven decisions, and contribute to our overall ML and data strategy. The ideal candidate must:

• Balance multiple perspectives, disagree, and commit when necessary to move key company decisions and critical priorities forward.
• Ability to work independently in a dynamic environment and proactively approach problem-solving.
• Be committed to driving positive business outcomes through expert data handling and analysis.
• Be an example for fellow engineers by showcasing customer empathy, creativity, curiosity, and tenacity.
• Have strong analytical and problem-solving skills, with the ability to innovate and adapt to fast-paced environments.

What You'll Do

• Modernize Signifyd’s Machine Learning (ML) Platform to scale for resiliency, performance, and operational excellence, working closely with Engineering and Data Science teams across Signifyd’s R&D group.
• Work alongside ML Engineers, Data Scientists, and other Software Engineers to develop innovative big data processing solutions for scaling our core product for eCommerce fraud prevention.
• Contribute to all processes of the ML lifecycle: data collection, annotation, modeling, evaluation, deployment, and monitoring.
• Write production-quality code for ML models as online services and APIs.
• Implement data and ML processing solutions for offline, batch, and real-time use cases.
• Mentor and coach fellow engineers on the team, fostering an environment of growth and continuous improvement.
• Identify and address gaps in team capabilities and processes to enhance team efficiency and success.
• Automate monitoring of model performance and user behavior.
• Take ownership of solutions from analysis to implementation.
• Influence the tooling, frameworks, and ML practices with the ML teams.
• Stay updated with the latest in Data Science and ML tooling & communities
• Present complex analyses clearly and concisely.

What You'll Need

• Ideally has 3-7 years of experience in data/ML engineering. Has experience navigating the challenges of working with large-scale data processing systems.
• Experience in contributing toward or building low-latency, high-availability data stores for real-time or near-real-time data processing with programming languages such as Python, Scala, Java, or JavaScript/TypeScript, as well as data retrieval using SQL and NoSQL.
• Hands-on expertise in data technologies with proficiency in Spark, Airflow, Databricks, AWS services (S3, EMR, SQS, Kinesis, etc.), and Kafka. Understand the trade-offs of various architectural approaches and recommend solutions suited to our needs.
• Experience in programming languages such as Java, Python, or Scala and experience understanding Cloud infrastructure environments including Kubernetes and Serverless.
• Working knowledge of ML algorithms, clustering algorithms, and binary classifiers (such as XGBoost)
• Solid knowledge of ML principles applied to recommendation systems.
• Familiarity with relational databases (Postgres, MySQL, etc).
• Experience using feature stores is a plus: homegrown solutions or commercial and open-source products like Tecton and Chronon.