Match score not available

Senior Machine Learning Engineer

extra holidays
Remote: 
Full Remote
Contract: 
Salary: 
10 - 200K yearly
Experience: 
Senior (5-10 years)
Work from: 

Offer summary

Qualifications:

5+ years in Fraud or FinTech, Strong Python and SQL skills, Experience with cloud platforms.

Key responsabilities:

  • Design, develop, implement ML solutions
  • Enhance backend systems for efficiency
  • Engage with large-scale data sets
  • Collaborate cross-functionally for model enhancement
  • Establish ML observability for model reliability
Sardine logo
Sardine Fintech: Finance + Technology Scaleup https://www.sardine.ai/
51 - 200 Employees
See more Sardine offers

Job description

Who we are:

We are a leader in financial crime prevention. Using unparalleled device intelligence and behavior biometrics, we apply machine learning to detect and stop fraud before it happens. The platform includes tools for identity verification, fraud prevention and investigation, AML monitoring, and case management. Over 250 companies use Sardine to prevent fake account creation, social engineering scams, account takeovers, bot attacks, payment fraud, and money laundering. We raised $75M, led by Andreessen Horowitz Growth, XYZ Capital, Google Ventures, Visa, Activant Capital, Experian, and ING Ventures.

Our culture:

  • We have hubs in the Bay Area, NYC, Austin, and Toronto. However, we have a remote-first work culture. #WorkFromAnywhere

  • We hire talented, self-motivated people and get out of their way

  • We value performance and not hours worked. We believe you shouldn't have to miss your family dinner, your kid's school play, or doctor's appointments for the sake of adhering to an arbitrary work schedule.

Location:

  • Remote - Canada or United States

  • From Home / Beach / Mountain / Cafe / Anywhere!

  • We are a remote-first company with a globally distributed team. You can find your productive zone and work from there.

About the role:

As a Machine Learning Engineer, you will play a pivotal role in designing, developing, and implementing cutting-edge machine learning solutions to mitigate fraud and risk, ensuring optimal outcomes for both our company and clients. Collaborating closely with cross-functional teams, you will contribute to the development of robust machine learning infrastructure and feature engineering capabilities.

You will:

  • Design, develop, and implement machine learning models and algorithms utilizing Python and SQL.

  • Enhance backend systems for feature processing and model serving, optimizing efficiency and reliability.

  • Engage with large-scale data sets, data pipelines, and data warehousing tools to extract meaningful insights.

  • Collaborate with data scientists, software engineers, data analysts, account managers, and product managers to identify business challenges, devise solutions, and iteratively enhance machine learning models.

  • Establish and fortify ML observability to ensure machine learning models' steadfast performance and reliability in production.

  • Build scalable and efficient machine learning infrastructure utilizing advanced tools such as Vertex AI, Apache Beam, and Kubeflow.

  • Develop software systems and libraries to bolster machine learning applications and streamline integration.

  • Conduct experiments, execute statistical analyses, and assess model performance to optimize accuracy, reliability, and speed.

An ideal candidate has:

  • 5+ years of hands-on experience in Machine Learning or related roles within Fraud, Risk, Compliance, Payments, or FinTech domains.

  • Extensive knowledge and educational background in computer science, machine learning, and statistics.

  • Strong programming proficiency in Python and SQL, coupled with hands-on experience in backend development.

  • Proficiency in data warehousing, data pipelines, and ETL tools, with a proven track record of managing the machine learning lifecycle.

  • Experience with cloud computing platforms such as GCP, AWS, or Azure.

  • Familiarity with Kubernetes or Docker for efficient containerization.

  • Proven track record of collaboration with data scientists to build, deploy, and refine machine learning models.

  • Prior experience in building ML observability to uphold the performance and reliability of machine learning models in production.

Compensation: Base pay range of $160,000 - $200,000 + Series B equity with tremendous upside potential + Attractive benefits

Benefits we offer:

  • Generous compensation in cash and equity

  • 7-years for post-termination option exercise (vs. standard 90 days)

  • Early exercise for all options, including pre-vested

  • Work from anywhere: Remote-first Culture

  • Flexible paid time off

  • Health insurance, dental, and vision coverage for employees and dependents - US and Canada specific

  • 4% matching in 401k / RRSP - US and Canada specific

  • MacBook Pro delivered to your door

  • One-time stipend to set up a home office — desk, chair, screen, etc.

  • Monthly meal stipend

  • Monthly social meet-up stipend

  • Annual health and wellness stipend

  • Annual Learning stipend

  • Unlimited access to an expert financial advisory

Join a fast-growing company with world-class professionals from around the world. If you are seeking a meaningful career, you found the right place, and we would love to hear from you.

Required profile

Experience

Level of experience: Senior (5-10 years)
Industry :
Fintech: Finance + Technology
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Adaptability
  • Problem Solving
  • Communication
  • Collaboration

Machine Learning Engineer Related jobs