Staff Machine Learning Engineer, Risk AI/ML: EVENT (Remote - US) at Jobgether

, , United States -

Full Time

Start Date

Immediate

Expiry Date

18 Feb, 26

Salary

0.0

Posted On

20 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, AI, Deep Learning, NLP, Graph Neural Networks, Risk Detection, Python, TensorFlow, PyTorch, Problem Solving, Technical Leadership, Collaboration, Communication, Feature Pipelines, Model Serving, MLOps

Industry

Internet Marketplace Platforms

Description

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Staff Machine Learning Engineer, Risk AI/ML: EVENT in United States. As a Staff Machine Learning Engineer on the Risk AI/ML team, you will take ownership of critical risk domains, building sophisticated AI/ML models that protect users and the business from financial threats, including fraud, scams, and account takeovers. You will architect, design, and deploy real-time, near-real-time, and scheduled risk-detection workflows, collaborating closely with platform, product, analyst, and operations teams. This role provides an opportunity to influence technical strategy at an organizational level, mentor other engineers, and solve complex challenges using advanced ML techniques such as deep learning, NLP, Graph Neural Networks, and LLMs. You will operate in a fast-paced, high-impact environment that values precision, innovation, and proactive problem-solving. Your work will directly enhance the security, trust, and scalability of the platform while supporting the development of future products and features. This position requires a strong commitment to excellence, technical leadership, and collaboration across diverse teams. Accountabilities: • Own and lead technical strategy for a critical risk domain (e.g., scams, account takeover), designing and building all models in the space. • Architect and design complex, cross-team risk detection systems, including feature pipelines, model selection, and high-performance serving. • Apply advanced AI/ML methodologies such as deep learning, NLP, GNNs, sequence modeling, and LLMs to solve domain-specific challenges. • Build context-aware risk systems that dynamically balance security measures with user experience. • Mentor and provide technical leadership to senior, mid-level, and junior engineers on the team. • Collaborate with product, operations, and cross-functional teams to translate business needs into actionable technical roadmaps. • Continuously improve ML pipelines, deployment processes, and system reliability while ensuring scalability. • 8–10+ years of professional experience in software engineering and/or AI/ML, with demonstrated production deployment of ML systems. • Proven technical leadership, including leading teams or pods and designing large-scale, cross-team ML systems from scratch. • Deep expertise in applied AI/ML techniques, including risk ML, deep learning, NLP, recommender systems, anomaly detection. Prior domain experience in Payment Risk, Credit Risk, or Identity Risk is required. • Expert-level coding skills (Python preferred) and experience with ML frameworks such as TensorFlow or PyTorch. • Strong problem-solving skills, technical judgment, and ability to operate independently and collaboratively. • Excellent communication skills to convey complex technical concepts to both technical and non-technical audiences. • Commitment to protecting users and upholding platform integrity, with a passion for innovative, high-quality engineering solutions. Nice to Have: • Master’s or Ph.D. in Computer Science, AI/ML, Data Science, or a related field. • Experience with modern AI/ML infrastructure (Feature Stores, Model Serving, Airflow, Spark, Kafka). • Familiarity with Graph Neural Networks, sequential models, or LLMs. • Knowledge of MLOps best practices, monitoring, and improving production ML models. • Experience with data visualization and analysis tools. • Competitive salary with bonus and equity eligibility. • Comprehensive health, dental, and vision benefits. • Flexible work arrangements with a hybrid approach, including required in-person participation for team offsites. • Paid time off and parental leave. • Retirement benefits (401(k) matching). • Professional growth and mentorship opportunities in a high-caliber, collaborative environment. • Inclusive culture that encourages innovation, diversity, and collaboration. Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching. When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly. 🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements. 📊 It compares your profile to the job’s core requirements and past success factors to determine your match score. 🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role. 🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed. The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, we share it directly with the company that owns the job opening. The final decision and next steps (such as interviews or additional assessments) are then made by their internal hiring team. Thank you for your interest! #LI-CL1

Responsibilities

As a Staff Machine Learning Engineer, you will lead the technical strategy for critical risk domains and design complex risk detection systems. You will mentor other engineers and collaborate with cross-functional teams to translate business needs into technical roadmaps.