Machine Learning Engineer
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:
Multiple career progression opportunities in a dynamic FULLY REMOTE 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)
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.
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:
Multiple career progression opportunities in a dynamic FULLY REMOTE 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)
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.
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:
Multiple career progression opportunities in a dynamic FULLY REMOTE 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)