Sr./Staff Machine Learning Engineer

About the role

Oscilar is building the next generation of AI-powered risk decisioning for fintech. Our platform helps financial institutions make faster, smarter decisions in real time. As we scale, machine learning sits at the core of what we do — and we are looking for an engineer who can help us build the infrastructure that makes it possible.

What You Will Do

• Scale and optimize existing ML systems.
• Improve the performance, reliability, and cost-efficiency of our current ML infrastructure, including feature stores, model serving, and orchestration pipelines.
• Build reproducible, automated ML pipelines.
• Design and operate the pipelines that power model training, deployment, and monitoring across the platform — so models ship reliably and repeatably, not as one-off integrations.
• Partner with data scientists to make low-latency production deployment a paved path.
• Build new ML infrastructure.
• Design and implement new components of our ML stack as the platform grows, with a focus on scalability, modularity, and developer experience.
• Own production reliability. Be responsible for the uptime, performance, and correctness of ML systems serving real-time, business-critical decisions.

Required

• 4+ years of experience building and maintaining production ML infrastructure.
• Strong software engineering fundamentals, with experience designing distributed systems and writing high-quality, maintainable code.
• Hands-on experience with the full ML lifecycle in production: feature engineering and serving, model deployment, monitoring, and retraining.
• Proficiency in Scala and Python, with hands-on experience building data and ML workloads on distributed processing frameworks such as Spark and Flink.
• Experience operating systems at scale, including performance tuning, observability, and incident response.
• Strong communication skills and the ability to collaborate effectively across data science, engineering, and product teams.
• Significant experience building and operating workloads on AWS.

Strongly Preferred

• Experience building ML infrastructure for fintech applications.
• Track record of scaling ML systems through significant growth in traffic, models, or feature volume.

Nice to Have

• Prior experience as an ML engineer at a startup.

Benefits

• Competitive salary and equity packages, including a 401k.
• Flexibility: Remote-first culture — work from anywhere.
• Health: 100% Employer covered comprehensive health, dental, and vision insurance with a top tier plan for you and your dependents (US).
• Balance: Unlimited PTO policy.
• Technical: AI First company; both Co-Founders are engineers at heart; and over 50% of the company is Engineering and Product.
• Culture: Family-Friendly environment; Regular team events and offsites.
• Development: Unparalleled learning and professional development opportunities.
• Impact: Making the internet safer by protecting online transactions.