Job Title: Principal / Senior Machine Learning Engineer
Position Type: FTE
Location: San Francisco / Portland, ME / Boston / Chicago / Seattle
Salary Range: $200,000 - $270,000 (USD)
Job ID#: 155325
Contact:
Job Description:
These are high-impact leadership roles focused on designing, deploying, and optimizing fraud detection models for large-scale payment systems. You'll work at the intersection of machine learning, cloud infrastructure, and risk engineering.
- Serves as the official payment partner of the U.S. federal fleet
- Powers 98% of gas station payment transactions nationwide
Responsibilities:
- Design, implement, train, and maintain machine learning algorithms and ML system pipelines.
- Work closely with our AI platform team and engineering teams to integrate AI components and models into our systems.
- Manage version control using GitHub and implement CI/CD pipelines for continuous integration and delivery.
- Design and implement RESTful APIs for system communication and operation.
- Collaborate with cross-functional teams, participate in code reviews, and communicate solutions to both technical and non-technical stakeholders.
Requirements:
- 10-20 years of working experience
- Minimum 5 years of application development experience using Python
- Minimum 3 years of experience building, training, and deploying machine learning models
- Strong proficiency with Python libraries such as Pandas, Numpy, and deep learning frameworks like PyTorch or TensorFlow
- Bachelor's Degree in Computer Science, Engineering, or related field
- Familiarity with cloud platforms (AWS, Azure, GCP) and infrastructure as code (Terraform)
- Experience applying DevOps principles
- Proficiency with GitHub and version control
- Excellent problem-solving skills and proactive approach
- Experience in the financial industry is a plus
About Us:
Founded in 2009, IntelliPro is a global leader in talent acquisition and HR solutions, operating in over 160 countries. We are committed to diversity, inclusivity, and providing rewarding employment opportunities. Learn more at .
Compensation:
The salary will be determined based on factors such as education, experience, location, and certifications. We offer a comprehensive benefits package, subject to eligibility.
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