Senior Machine Learning Engineer

You will lead the design, development, and deployment of machine learning systems that power personalization, search, and marketplace optimization. You will work across the full ML lifecycle—from data exploration and modeling to productionization and monitoring—while partnering closely with cross-functional teams to align technical solutions with business needs.

• Design and improve recommendation, ranking, and search systems to enhance product discovery and user engagement
• Develop and deploy ML models for personalization, inventory valuation, classification, and demand forecasting
• Build and maintain scalable data models and pipelines using Snowflake and Python-based workflows
• Own experimentation frameworks, including A/B testing, KPI definition, and performance evaluation of ML systems
• Deploy models into production environments and ensure reliability, observability, and version control best practices
• Collaborate with Product, Engineering, Design, and Marketing teams to translate business needs into data-driven solutions
• Develop advanced analytics capabilities such as embeddings, user-to-item mapping, and fraud detection signals
• Continuously improve model performance through iteration, monitoring, and optimization of data and features

Requirements:

The ideal candidate brings extensive experience building and scaling machine learning systems in production, particularly in consumer-facing or marketplace environments. You combine strong theoretical foundations in statistics and ML with practical engineering skills and a product-oriented mindset.

• 8+ years of experience in machine learning, data science, or quantitative engineering roles
• Expert-level proficiency in Python for ML model development and data manipulation
• Strong experience with SQL and data warehousing environments such as Snowflake
• Deep understanding of recommendation systems, ranking models, and personalization techniques
• Experience with causal inference, experimentation design, and statistical modeling
• Familiarity with embeddings, vector search, and semantic similarity techniques
• Experience deploying ML models into production and working with modern data stacks (e.g., dbt, Git, cloud infrastructure)
• Strong communication skills with the ability to explain complex technical concepts to non-technical stakeholders
• Experience working in fast-paced, high-growth environments (marketplaces, e-commerce, or consumer platforms preferred)
• Proven ability to lead projects independently and mentor other engineers or data scientists

Benefits:

• Competitive salary based on geographic location and experience, with U.S. ranges up to approximately $197,200 USD
• Equity participation in a high-growth technology company
• Comprehensive medical, dental, and vision insurance coverage
• 401(k) retirement plan with company contributions
• Unlimited paid time off plus company holidays
• Paid parental leave for eligible employees
• Remote-friendly work environment with flexible arrangements
• Professional development support, learning resources, and growth opportunities
• Additional lifestyle and wellness benefits depending on location.

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

 Why Apply Through Jobgether? 

 

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