Machine Learning Engineer- Cloud Deployment
1 week ago
San Francisco CA, San Francisco County, CA; California, United States
Cyber Security Services
Full-time
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Own the design, training and production deployment of machine learning systems behind a core detection capability. Partner closely with technical leadership and help set engineering standards on a small, fast-moving team.
What You'll Do
Design and build machine learning models that flag suspicious activity as it happens. Architect systems that can absorb significant growth in data volume and traffic. Talk with customers to understand the threats they face and uncover new signals that strengthen detection. Set technical patterns , push for correctness and raise the quality bar across the team. Own systems end to end , from data pipelines through serving and infrastructure. What We're Looking For 4+ years of machine learning engineering experience, including shipping models to production at scale. Experience training and deploying models, with good judgment about which approach fits a problem and where its limits lie. Strong engineering fundamentals, including clean production-grade Python and end-to-end system ownership. Hands-on background with low-latency data processing and scalable storage and compute systems. Fast learner who ships quickly and is comfortable in a small, high-autonomy team. Pride in craft and in building things that hold up over time. Bonus Points Background in high-stakes domains such as quantitative finance or fraud detection. Experience shipping production machine learning at an early-stage company or on an ML infrastructure team. Degree in computer science, math or a quantitative field. First-author publication at a leading machine learning conference. Benefits Health, dental and vision coverage On-site, 5 days per week in office Full-time Compensation, As The Posting Describes It Equity Retirement plan Commission Cyber Security Services
What You'll Do
Design and build machine learning models that flag suspicious activity as it happens. Architect systems that can absorb significant growth in data volume and traffic. Talk with customers to understand the threats they face and uncover new signals that strengthen detection. Set technical patterns , push for correctness and raise the quality bar across the team. Own systems end to end , from data pipelines through serving and infrastructure. What We're Looking For 4+ years of machine learning engineering experience, including shipping models to production at scale. Experience training and deploying models, with good judgment about which approach fits a problem and where its limits lie. Strong engineering fundamentals, including clean production-grade Python and end-to-end system ownership. Hands-on background with low-latency data processing and scalable storage and compute systems. Fast learner who ships quickly and is comfortable in a small, high-autonomy team. Pride in craft and in building things that hold up over time. Bonus Points Background in high-stakes domains such as quantitative finance or fraud detection. Experience shipping production machine learning at an early-stage company or on an ML infrastructure team. Degree in computer science, math or a quantitative field. First-author publication at a leading machine learning conference. Benefits Health, dental and vision coverage On-site, 5 days per week in office Full-time Compensation, As The Posting Describes It Equity Retirement plan Commission Cyber Security Services