Senior Software Engineer, ML Engineering

<h3>Who Are You</h3> <p>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:</p> <br/> <ul> <li>Balance multiple perspectives, disagree, and commit when necessary to move key company decisions and critical priorities forward.</li> <li>Ability to work independently in a dynamic environment and proactively approach problem-solving.</li> <li>Be committed to driving positive business outcomes through expert data handling and analysis.</li> <li>Be an example for fellow engineers by showcasing customer empathy, creativity, curiosity, and tenacity.</li> <li>Have strong analytical and problem-solving skills, with the ability to innovate and adapt to fast-paced environments.</li> </ul> <h3>What You'll Do</h3> <ul> <li>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&amp;D group.</li> <li>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.</li> <li>Contribute to all processes of the ML lifecycle: data collection, annotation, modeling, evaluation, deployment, and monitoring.</li> <li>Write production-quality code for ML models as online services and APIs.</li> <li>Implement data and ML processing solutions for offline, batch, and real-time use cases.</li> <li>Mentor and coach fellow engineers on the team, fostering an environment of growth and continuous improvement.</li> <li>Identify and address gaps in team capabilities and processes to enhance team efficiency and success.</li> <li>Automate monitoring of model performance and user behavior.</li> <li>Take ownership of solutions from analysis to implementation.</li> <li>Influence the tooling, frameworks, and ML practices with the ML teams.</li> <li>Stay updated with the latest in Data Science and ML tooling &amp; communities</li> <li>Present complex analyses clearly and concisely.</li> </ul> <h3>What You'll Need</h3> <ul> <li>Ideally has 3-7 years of experience in data/ML engineering. Has experience navigating the challenges of working with large-scale data processing systems.</li> <li>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.</li> <li>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.</li> <li>Experience in programming languages such as Java, Python, or Scala and experience understanding Cloud infrastructure environments including Kubernetes and Serverless.</li> <li>Working knowledge of ML algorithms, clustering algorithms, and binary classifiers (such as XGBoost)</li> <li>Solid knowledge of ML principles applied to recommendation systems.</li> <li>Familiarity with relational databases (Postgres, MySQL, etc).</li> <li>Experience using feature stores is a plus: homegrown solutions or commercial and open-source products like Tecton and Chronon.</li> </ul> <strong><span>#LI-Hybrid</span></strong> <p>Benefits:</p> <ul> <li>Stock Options</li> <li><em>Annual Performance Bonus or Commissions</em></li> <li>Pension matched up to 3%</li> <li>‘Day one’ access to great health insurance scheme</li> <li><em>Enhanced maternity and paternity leave (12 weeks full-pay for mums &amp; dads)</em></li> <li>Paid team social events</li> <li>Headspace Benefits</li> <li>Dedicated learning budget through Learnerbly</li> </ul> <p><a href="https://drive.google.com/file/d/1HSnMY6HGjB1FNRX4Ez9bUre5mrPPcHIq/view?usp=sharing" target="_blank">Signifyd's Applicant Privacy Notice</a></p>