Machine Learning Engineer

Trusted by many of the largest companies globally, Accertify is the leading digital platform assessing risk across the entire customer journey, from Account Monitoring and Payment Risk to Refund Fraud and Dispute Management. Accertify helps maximize revenues and user experience while minimizing loss and customer friction. We offer ultra-fast decision-making and precise control, ensuring our customers are always confidently in the driver’s seat and ready to #MoveAtTheSpeedOfRight.

Be in the driver’s seat of your career as a Machine Learning Engineer with the industry leader- and build a career you can trust.

The Machine Learning Engineer will design and deliver high-impact machine learning solutions and tools that push the boundaries of what is possible in a high-performance production setting. In this role, you will tackle complex challenges, delivering transformative machine learning projects that set new standards of excellence and make a lasting impact.

Essential Duties & Responsibilities

• Own and develop the existing ML model monitoring and reporting codebase, aligning with the existing MLOps framework
• Collaborate with cross-functional teams to optimize data pipelines through data validation, data profiling, data versioning, and model monitoring
• Design, develop, test, deploy, and maintain scalable, secure software for batch and real-time ML pipelines in a high-throughput and low-latency production environment
• Demonstrate subject matter expertise and ownership for your team’s services
• Present results to stakeholders and executives as needed
• Collaborate with the Data Science, Big Data, and DevOps teams
• Elevate team performance through mentoring, training, code reviews, and unit testing
• Take ownership of initiatives, propose solutions, and be accountable for projects from inception to completion.
  
  

Skills & Qualifications

• 2 years of software engineering experience in an enterprise setting
• Strong Relational database skills in SQL, such as JDBC/Oracle or PostgreSQL
• Experience in deploying ML models in production and familiarity with MLOps
• Experience working with a larger ML/ Engineering team, documenting code, performing peer code reviews, writing unit tests, and following an SDLC
• 1 years of experience in Spark and/or NoSQL databases
• Experience in Python and Spark (PySpark)
• Bachelor's degree in computer science or equivalent
  
  

Preferred Qualifications

• High-volume transactional environment experience
• Big Data components/frameworks, such as HDFS and Spark 3.0, etc
• Understanding statistics and Machine Learning concepts such as traditional ML algorithms, Generative ML algorithms, Concept drift and decay, A|B Testing etc.
  
  

Additional Details

• Potential salary range: $80-100K. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
• This role is eligible for remote US-based (work-from-home) locations. Chicago-based candidates would work in a hybrid capacity from Accertify's headquarters in Itasca, IL.
• Visa Sponsorship: Employment eligibility to work for Accertify in the U.S. is required, as Accertify will not pursue Visa sponsorship for this position.
  
  

Why Join Accertify?

Benefits

At Accertify, we believe in investing in our people. We offer a comprehensive suite of benefits to support your success both professionally and personally:

• Health & Wellness: Medical, dental, and vision coverage for you and your family.
• Time Off: Paid time off, holidays, and personal days to maintain work-life balance.
• Financial Growth: We offer competitive compensation, performance-based rewards, and local retirement or savings plans where applicable, along with financial education resources. 
• Career Development: Training programs, mentorship opportunities, and growth potential within the company.
• Wellness Support: Mental health resources and wellness programs.
• Family-Friendly Perks: Parental leave, flexible work arrangements.
• Extras & Perks: Commuter benefits, employee discounts, and company-sponsored events.