Senior ML Engineer Advertising at eBay Amsterdam Hybrid Role

📍 Location: nl

🏷 Type: Not specified

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Job Overview

This Senior-Level Machine Learning Engineer role at eBay focuses on building scalable systems within the digital advertising and ecommerce ML domain. You will design and deploy models powering ad ranking, recommendation engines, and advertiser optimization systems. Ideal for candidates with 5+ years experience, this role suits engineers who combine strong production ML expertise with data-driven decision-making. You will operate at the intersection of large-scale data systems, deep learning, and GenAI innovation in a high-impact monetization environment.

🌍 Work Eligibility & Location

This role is based in Amsterdam with a Hybrid setup, making it accessible to EU-based candidates or those open to relocation. While visa sponsorship is not explicitly guaranteed, companies like eBay often support high-impact hires. For international applicants, securing eligibility to work in the Netherlands significantly improves chances. The role requires strong English communication skills and alignment with European work hours.

💰 Salary Intelligence

Although no official salary is listed, similar Senior ML Engineer roles in Amsterdam at top-tier tech firms typically range between €90K and €130K, often including bonuses and stock options. Given eBay’s scale and the revenue-critical nature of advertising systems, compensation is likely competitive within the European big tech market. Candidates with strong production ML and distributed systems expertise can negotiate toward the upper band.

📊 Role Breakdown

This role is heavily focused on production-grade machine learning systems, with approximately 40% of time spent on designing and deploying ML models for ad ranking and recommendation systems using Python, PyTorch, and Hugging Face. Around 25% involves data analysis and experimentation, leveraging SQL, large-scale datasets, and A/B testing frameworks to optimize performance metrics such as revenue and relevance. Another 20% is dedicated to system optimization, focusing on latency, throughput, and scalability using technologies like Spark and Hadoop.

The remaining 15% includes cross-functional collaboration and mentoring, working closely with product managers and researchers to translate business goals into ML solutions. A key differentiator is the application of GenAI techniques and advanced optimization strategies to improve advertiser outcomes. This is not a research-only role—it requires strong ownership across the end-to-end ML lifecycle, from feature engineering to monitoring deployed systems in production.

🧩 Required Skills & Fit

📈 Difficulty & Competitiveness

This is a high-difficulty role requiring both depth and breadth. The 5+ years experience threshold filters out early-career applicants, while the requirement for production ML systems expertise significantly raises the bar. Candidates must demonstrate not just model development but also scalable deployment and system optimization. Competition is intense due to eBay’s brand and the strategic importance of advertising, attracting top-tier engineers globally.

🚀 Career Impact

This role delivers strong career acceleration through exposure to large-scale ML infrastructure and high-revenue systems. Working on advertising directly impacts business outcomes, strengthening your profile for senior and staff-level roles. The integration of GenAI and optimization systems positions you at the forefront of applied AI, making you highly competitive for future roles in both big tech and AI-first companies.

📋 Key Responsibilities

You will design and deploy machine learning models for ad ranking and recommendation using PyTorch and Python. A major focus is to analyze large-scale datasets with SQL and define optimization strategies. You will own the full ML lifecycle, including feature engineering, model training, and monitoring in production environments. The role requires you to optimize system performance by improving latency, throughput, and reliability using distributed technologies like Spark. Additionally, you will collaborate cross-functionally with product and research teams and mentor junior engineers, while applying GenAI techniques to enhance advertiser and buyer experiences.

🎯 Application Strategy

🧠 Application Optimization (Adaptive)

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🧠 Fit & Positioning Analysis

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📅 Application Signals

This role was posted recently, indicating high urgency in hiring. Given the competitive senior talent market and the strategic importance of advertising at eBay, early applications significantly improve visibility. Expect a structured hiring process focusing on system design, ML depth, and business impact. Applying within the first 1–2 weeks is strongly recommended.

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✅ Job Source & Verification

This job listing originates from the official eBay careers platform, ensuring high source credibility and accuracy. The role was last updated 4 days ago, confirming that it is actively hiring. Candidates should rely on the official posting for final application details and monitor updates for any changes in requirements or hiring status.