oscilar - Sr./Staff Machine Learning Engineer
Requirements
• 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. • Prior experience as an ML engineer at a startup.
Responsibilities
• 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. • Set ML engineering standards. Help define best practices for model deployment, monitoring, and lifecycle management. Mentor teammates and raise the bar across the organization. • Own production reliability. Be responsible for the uptime, performance, and correctness of ML systems serving real-time, business-critical decisions.
Benefits
• Compensation: 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
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