Senior Staff Machine Learning Engineer, Trust
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Staff Machine Learning Engineer, Trust based in the United States.
This role offers the opportunity to shape the future of trust and safety through advanced machine learning technologies at global scale. As a senior technical leader, you will design and deliver innovative ML solutions that help detect fraud, protect users, and improve platform integrity. You will work across engineering, product, operations, and data teams to solve complex challenges involving large-scale data, AI systems, and evolving risk landscapes. The position combines hands-on engineering, strategic technical leadership, and mentorship of other engineers. You will contribute to cutting-edge areas including generative AI, agentic AI, anomaly detection, and real-time risk evaluation. This is an impactful opportunity for an experienced ML expert to build production systems that strengthen trust across a worldwide platform.
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Staff Machine Learning Engineer, Trust based in the United States.
This role offers the opportunity to shape the future of trust and safety through advanced machine learning technologies at global scale. As a senior technical leader, you will design and deliver innovative ML solutions that help detect fraud, protect users, and improve platform integrity. You will work across engineering, product, operations, and data teams to solve complex challenges involving large-scale data, AI systems, and evolving risk landscapes. The position combines hands-on engineering, strategic technical leadership, and mentorship of other engineers. You will contribute to cutting-edge areas including generative AI, agentic AI, anomaly detection, and real-time risk evaluation. This is an impactful opportunity for an experienced ML expert to build production systems that strengthen trust across a worldwide platform.
Accountabilities:
- Define and execute the long-term machine learning technical vision and strategy for trust and safety initiatives, identifying key investments and designing scalable ML solutions.
- Lead the architecture, development, and productionization of advanced machine learning systems supporting fraud prevention, risk evaluation, and platform protection.
- Drive large-scale, multi-quarter machine learning initiatives that span multiple teams, aligning technical roadmaps with business and product objectives.
- Serve as a technical leader and mentor for machine learning and software engineers, providing guidance on complex modeling, architecture, and engineering challenges.
- Build and continuously improve machine learning models using large-scale structured and unstructured data to support product, business, and operational use cases.
- Develop, deploy, and operate ML pipelines and systems at scale across batch and real-time environments.
- Collaborate with software engineers, product managers, operations teams, and data scientists to identify opportunities, define requirements, and measure business impact.
- Partner with trust, risk, and platform teams to address evolving fraud threats and develop proactive defense strategies.
- Apply advanced AI techniques, including generative AI, agentic AI, natural language processing, computer vision, and anomaly detection, to solve complex problems.
- Establish engineering best practices around model development, experimentation, testing, deployment, and operational reliability.
- 12+ years of professional experience in applied machine learning or related engineering disciplines.
- Bachelor’s, Master’s, or PhD degree in Computer Science, Machine Learning, or a related technical field.
- 2–3+ years of experience working with large language models, generative AI technologies, and agentic AI frameworks, including architecture, orchestration, and production deployment.
- Strong programming skills in languages such as Python, Scala, Java, C++, or equivalent, along with strong data engineering capabilities.
- Deep understanding of machine learning principles, including feature engineering, model selection, training and serving optimization, A/B testing, and production ML best practices.
- Experience with machine learning algorithms and domains such as gradient boosted trees, neural networks, deep learning, natural language processing, computer vision, personalization, recommendation systems, and anomaly detection.
- Hands-on experience with technologies such as TensorFlow, PyTorch, Kubernetes, and modern ML infrastructure platforms.
- Proven experience building end-to-end machine learning systems, infrastructure, and production-grade models at scale.
- Familiarity with large-scale software architecture patterns, APIs, high-volume data pipelines, and efficient algorithm design.
- Experience with test-driven development, incremental delivery, experimentation frameworks, and deployment best practices.
- Experience in trust, fraud prevention, risk management, or security-related domains is a plus.
- Ability to work effectively as a senior individual contributor, influencing technical direction across multiple teams.
- Competitive base salary range of $244,000 - $305,000 USD, depending on experience, skills, location, and business needs.
- Eligibility for additional compensation opportunities including bonuses and equity.
- Comprehensive benefits package designed to support employee well-being and financial security.
- Employee travel credit benefits.
- Remote-eligible work environment with flexibility to work from approved locations in the United States.
- Opportunities to collaborate with global teams on high-impact technology initiatives.
- Access to challenging technical problems involving advanced AI, machine learning, and large-scale systems.
- Inclusive workplace culture focused on innovation, belonging, and diverse perspectives.
- Support for reasonable accommodations throughout the hiring process and employment experience.