Senior Staff Machine Learning Engineer, Trust
New
Remote-eligible work environment with flexibility to work from approved locations in the United States.Full-TimeSenior
SalaryCompetitive base salary range of $244,000 - $305,000 USD, depending on experience, skills, location, and business needs.
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Job Details
- Experience
- 12+ years
- Required Skills
- PythonJavaKubernetesPyTorchC++TensorflowScalaNLPGenerative AIComputer Vision
Requirements
- 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.
- Strong programming skills in languages such as Python, Scala, Java, C++, or equivalent.
- Deep understanding of machine learning principles including feature engineering, model selection, A/B testing, and production best practices.
- Experience with ML algorithms such as gradient boosted trees, neural networks, deep learning, NLP, computer vision, 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, and experimentation frameworks.
Responsibilities
- 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.
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