Sr. Staff Machine Learning Engineer

Role Overview

This senior-level role sits at the core of a fast-scaling fintech environment, where machine learning directly shapes product performance, risk intelligence, and customer experience. You will lead the end-to-end design and deployment of production-grade ML systems that operate at scale and deliver measurable business impact.

What You Will Do

Own the end-to-end lifecycle of machine learning systems, including data ingestion, preprocessing, model training, deployment, monitoring, and ongoing optimization in production environments. Design and maintain scalable and reliable data pipelines supporting large-scale model training and inference workflows.

Why It Might Be a Fit

This is a hands-on leadership role ideal for someone who thrives in building robust, scalable systems in dynamic, data-rich environments. You will have significant autonomy to define best practices for ML system design, monitoring, and lifecycle management.

Requirements

• Master’s or Ph.D. in Computer Science, Engineering, or a related technical field
• 6+ years of experience building and deploying machine learning systems in production environments
• Strong programming skills in Python and hands-on experience with ML frameworks such as TensorFlow, PyTorch, and scikit-learn
• Proven experience designing end-to-end ML pipelines, including data processing, model training, deployment, and monitoring
• Strong background in cloud platforms such as Amazon Web Services, Google Cloud, or Microsoft Azure
• Experience with distributed computing frameworks like Apache Spark and orchestration tools such as Kubernetes
• Strong knowledge of model optimization, CI/CD practices, version control, and MLOps principles
• Excellent analytical thinking, problem-solving skills, and ability to collaborate across cross-functional teams

Benefits

• Competitive compensation package aligned with market benchmarks and experience level
• Company equity enabling participation in long-term organizational growth
• Comprehensive medical, dental, and vision insurance coverage
• 401(k) retirement savings plan with employer match (for U.S.-based employees)
• Unlimited paid time off plus company holidays
• Parental leave and family-supportive policies
• Flexible remote-friendly work environment with occasional in-person onboarding and collaboration sessions
• Access to modern ML infrastructure, cloud platforms, and continuous learning opportunities