Machine Learning Engineer
Paysafe (“Paysafe”) (NYSE: PSFE) (PSFE.WS) is a leading payments platform with an extensive track record of serving merchants and consumers in the global entertainment sectors. Its core purpose is to enable businesses and consumers to connect and transact seamlessly through industry-leading capabilities in payment processing, digital wallet, and online cash solutions. With over 20 years of online payment experience, an annualized transactional volume of over $130 billion in 2022, and approximately 3,300 employees located in 12+ countries, Paysafe connects businesses and consumers across 100 payment types in over 40 currencies around the world. Delivered through an integrated platform, Paysafe solutions are geared toward mobile-initiated transactions, real-time analytics and the convergence between brick-and-mortar and online payments.
Further information is available at www.paysafe.com.
What to expect:
- Design and develop machine learning solutions for online payments financial crime prevention
- Bring state-of-the-art machine learning research into our financial crime prevention practice
- Drive innovation in using alternative data sources for financial crime prevention
- Work closely with operation teams, analyze financial crime patterns, and create and adapt machine learning based financial crime prevention mechanisms while focusing strongly on the customer’s experience and business growth
- Identify and qualify business opportunities and work with business and product teams to ensure machine learning solutions are addressing the correct business needs
- Provide machine learning expertise to support the technical relationship with Paysafe divisions, including solution briefings, proof-of-concept work, and partner directly with product management to prioritize solutions impacting our business performance
- Own machine learning systems end-to-end, from collecting data to deploying in production and monitoring
- Be responsible for the quality and ongoing evaluation of the machine learning systems
- Work closely with product and IT teams to successfully integrate machine learning systems into our products
- Recommend integration strategies, enterprise architectures, platforms, and application infrastructure required to successfully implement a complete solution
- Collaborate with other engineers to build common tools for accelerating machine learning operations internally
To be successful you need to have:
- MSc or PhD degree in Computer Science, Machine Learning, or related technical field
- Minimum 3 years of professional experience in machine learning
- Solid understanding of machine learning fundamentals
- Strong analytical skills
- Proven ability to implement, debug, and deploy machine learning systems in industry
- Experience in at least one of the following deep learning applications: Computer Vision, Natural Language Processing or Speech Recognition
- Familiarity with graph algorithms and graph databases
- Ability to conduct applied research and bring it to production solutions
- Proficiency in Python programing
- Proficiency in SQL
- Experience with Tensorflow/PySpark or another popular ML framework
- Experience working with cloud technology stack (AWS, Azure, etc.) and developing machine learning systems in a cloud environment
- Ability to write high-quality code
- Result oriented team player
- Strong communication skills and excellent spoken and written English
We offer in return:
- The opportunity to write the history of a leading and growing multinational company
- Tailor-made training and ongoing development to help you enhance your skills in the field of online payments
- Multiple career progression opportunities in a dynamic in-house business
- Environment where product expertise, professional and personal commitment are rewarded
- Competitive remuneration and social benefits package (25 days annual paid leave, health insurance, sports card, team events, company discounts, variety of soft skills, business and technical training programs)
- Fun and collaborative working atmosphere
- Flexible working model - we encourage our employees to embrace our flexible working approach. You will be expected to work from home and spend an average of three days a week at our Sofia office as part of our hybrid work model
Are you ready to take your career to the next level? Join our team that is inspired by a unified vision and propelled by passion.
Send your CV in English.
Only shortlisted candidates will be contacted for an interview.
Wondering how our interview process looks like now? Learn more here: https://bit.ly/paysafe_interviews
Equal Employment Opportunity
Paysafe provides equal employment opportunities to all employees, and applicants for employment, and prohibits discrimination of any type with regard to ethnicity, religion, age, sex, national origin, disability status, sexual orientation, gender identity or expression, or any other protected characteristics. This policy applies to all terms and conditions of recruitment and employment. If you need any reasonable adjustments please let us know. We will be happy to help and look forward to hearing from you.