Senior Staff Machine Learning Engineer, Trust at Jobgether – United States
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About This Position
This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior Staff Machine Learning Engineer, Trust in the United States.
This role offers a unique opportunity to shape the future of trust and safety across a large-scale, high-impact platform. As a senior technical contributor, you will design, build, and productionize cutting-edge Machine Learning and Agentic AI models to detect and prevent fraud, protect users, and enhance overall platform safety. You will influence long-term ML strategy, drive large-scale initiatives across multiple teams, and mentor other engineers while remaining hands-on in coding and model deployment. The position combines technical excellence with cross-functional collaboration, providing exposure to advanced AI technologies, high-volume data pipelines, and mission-critical ML infrastructure. You will contribute directly to protecting the community and improving operational outcomes at scale.
Define and execute the long-term Machine Learning technical vision for trust and safety initiatives, identifying key investments and championing best practices.
Lead the design, development, and productionization of ML models and pipelines, including batch and real-time use cases for anomaly detection, risk evaluation, and generative AI applications.
Drive multi-quarter, cross-team ML projects, ensuring alignment across product, platform, and trust engineering roadmaps.
Mentor and provide technical guidance to other ML and software engineers on complex architectural, modeling, and production challenges.
Collaborate with cross-functional partners—including software engineers, data scientists, and product managers—to translate requirements into scalable ML solutions.
Continuously evaluate emerging AI/ML technologies to advance capabilities, model performance, and operational reliability.
Contribute hands-on code and actively participate in building robust, scalable, and maintainable ML systems.
Requirements:
12+ years of industry experience in applied Machine Learning, with 2–3+ years working with LLMs and generative AI technologies, including Agentic AI frameworks.
Bachelor’s, Master’s, or PhD in Computer Science, Machine Learning, or a related field.
Strong programming skills in Python, Scala, Java, C++, or equivalent, with solid data engineering expertise.
Deep understanding of ML best practices (training/serving skew minimization, feature engineering, model selection) and algorithms (gradient boosted trees, neural networks, deep learning).
Hands-on experience with ML frameworks and tools such as TensorFlow, PyTorch, and Kubernetes, as well as end-to-end ML infrastructure and production systems.
Familiarity with large-scale software application architecture, including APIs, high-volume data pipelines, and efficient model deployment.
Experience with test-driven development, A/B testing, and incremental deployment.
Prior experience in Trust, Risk, fraud detection, or safety domains is a plus.
Excellent collaboration, communication, and mentoring skills.
Benefits:
Competitive base salary range: $244,000 – $305,000 USD, dependent on experience and skills.
Performance-based bonuses, equity, and other incentive programs.
Comprehensive health, dental, and vision insurance coverage.
Flexible remote work options and paid time off.
Access to advanced AI/ML tools, high-scale platforms, and cutting-edge technologies.
Opportunities for career growth, skill development, and mentorship in a highly innovative environment.