FICO
FinTech
MLEngineer
Neural analysis suggests this role is
optimal for Mid+ candidates.
“ML Engineer at FICO. Skills: Machine Learning, Distributed Systems, Cloud Engineering, Software Development. Design and implement scalable ML systems. Develop and maintain ML models”
What You'll Achieve.
Improve model accuracy; Reduce latency; Increase system reliability; Deliver high-quality software
Industry & Context.
Root cause analysis; Troubleshooting; Analytical problem solving
What They're Looking For.
Must Have
5+ years of experience in software development, Experience with Python and Java, Experience with cloud platforms (AWS, Azure, or GCP), Experience with containerization technologies (Docker, Kubernetes), Experience with CI/CD pipelines, Experience with relational databases (e.g., PostgreSQL, MySQL), Experience with NoSQL databases (e.g., MongoDB, Cassandra), Experience with distributed systems, Experience with machine learning frameworks (e.g., TensorFlow, PyTorch), Experience with data processing frameworks (e.g., Spark, Flink), Experience with version control systems (e.g., Git)
Nice to Have
Master's degree or PhD in Computer Science or related field, Experience with MLOps practices, Experience with real-time data processing, Experience with graph databases, Experience with message queues (e.g., Kafka, RabbitMQ), Experience with infrastructure as code (e.g., Terraform, CloudFormation), Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack), Experience with security best practices, Contributions to open-source projects
What You'll Do.
Design and implement scalable ML systems
Develop and maintain ML models
Build and manage data pipelines
Deploy and monitor ML models in production
Collaborate with cross-functional teams
Optimize ML system performance
Troubleshoot and resolve issues
Stay up-to-date with ML advancements
How You'll Work.
Team & Collaboration
Cross-functional teams; Product managers; Data scientists; Software engineers
Communication Scope
Technical documentation; Presentations
Process & Methodology
Agile methodologies, Scrum
Full Job Description
**FICO (NYSE: FICO)** is a leading global analytics software company, helping businesses in 100+ countries make better decisions. Join our world-class team today and fulfill your career potential! **The ****Opportunity** In this role, you will be a member of a highly talented team of engineers and scientists enabling advanced predictive models deployed into cloud-based real-time transaction processing systems. You will be a contributor to FICO products and strategic initiatives that involve analytic innovation with a strong focus on building, testing, and deploying advanced analytics for the FICO Platform. You will have the opportunity to build industry leading solutions and stay at the forefront of modern AI and ML technologies. **What You’ll Contribute** * Contribute to the requirements and development of advanced distributed ML architectures, pipelines, tools, infrastructure, and algorithms that scale up to support both production execution and development of real-time predictive analytics on large volumes of high-throughput transactional data. * Integrate and evaluate advanced ML technologies, platforms and frameworks. Balance performance and cost constraints. Establish strong processes, quality controls, and ethical standards for PII and IP protection, analytic development, and product delivery. * Interact and collaborate with cross functional teams (Software Development, QA, Professional Services, IT, Product Management, Sales, and Product Support), drive and influence analytic and software designs decisions to ensure successful integration of analytic models into FICO Platform. * Mentor junior engineers and scientists. * Travel and work outside of normal business hours as business dictates. **What We’re ****Seeking** * M.S. or Ph.D. degree in computer science, engineering, physics, or a related technical field * Industry experience with a proven success record in analytic software, data engineering, or machine learning; experience working with cloud-based and
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