Software Engineer, ML Engineering

Signifyd

We switched to a 4 day work week in January 2022 (32hrs / week)

Only considering candidates eligible to work in Budapest, Hungary ⚠️

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.

#LI-Hybrid

Benefits:

  • Stock Options
  • Annual Performance Bonus or Commissions
  • Pension matched up to 3%
  • ‘Day one’ access to great health insurance scheme
  • Enhanced maternity and paternity leave (12 weeks full-pay for mums & dads)
  • Paid team social events
  • Mental wellbeing resources
  • Dedicated learning budget through Learnerbly

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Signifydsignifyd.com

Optimize Revenue + Automate Orders + Eliminate Fraud

Working Week

We switched to a 4 day work week in January 2022 (32hrs / week)

  • Mon
  • Tue
  • Wed
  • Thu
  • 🏖️
    Fri

Our Vacation Policy

Our vacation policy varies by location e.g. in the USA we offer Discretionary Time Off Policy (unlimited) and in the UK we offer 20 days PTO plus public holidays. For the UK this works out as:

  • 28 days
  • 52 Fridays
  • 80 days off per year

Remote Working Policy

We have offices in San Jose, New York, Denver, Belfast, London, Sao Paulo and Mexico City. Many of us also work 100% remotely.

Company Benefits

  • Health insurance
  • 401K Match
  • Generous parental leave
  • Dentalcare
  • Equity / options
  • Equipment allowance

Our Team

We're a team of 550 across 19 departments:

  • engineering
    128
  • data science
    66
  • sales
    50
  • support
    44
  • operations
    24
  • business development
    22
  • marketing
    22
  • +12 more teams

Desirable Skills and Experience

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