Staff Machine Learning Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Lead the creation of sophisticated machine learning and AI models for marketplace algorithms, including search ranking, recommendations, and matching solutions.

• Design and implement effective MLOps practices for seamless model deployment and scalability, encompassing self-hosted LLMs.

• Automate the model training process and post-training activities, including fine-tuning, RLHF/preference alignment, and distillation.

• Enhance model runtime performance and manage inference costs.

• Oversee the entire MLOps lifecycle, which includes data pipelines, experiment tracking, CI/CD, model registry, monitoring, and rollback procedures.

• Define and manage evaluation frameworks for deep learning and ML systems.

• Establish offline metrics, conduct online experimentation, A/B testing, guardrail metrics, and specific evaluations for LLMs.

• Collaborate with engineers, ML infrastructure teams, data scientists, and product managers to develop scalable ML systems.

• Create a long-term technical vision and roadmap for the team.

• Design and launch new products and features while enhancing existing products with ML capabilities.

• Mentor junior team members and promote knowledge sharing.

⛳️ Requirements

• Master's or Ph.D. in a quantitative field such as Computer Science, Statistics, Mathematics, or a related discipline.

• Over 6 years of experience in data science and machine learning.

• Hands-on experience with post-training and self-hosting open-weight LLMs, including fine-tuning, quantization, and serving infrastructure such as vLLM or SGLang.

• In-depth understanding of evaluation metrics for both deep learning and classical machine learning.

• Comprehensive fluency in the MLOps lifecycle, covering data versioning, feature stores, CI/CD for ML, model monitoring/observability, and retraining pipelines.

• Knowledge of large-scale distributed application architecture, design, implementation, and performance optimization.

• Capability to steer the roadmap and strategy for scalable, production-quality systems.

• Practical expertise in advanced machine learning algorithms and deep learning for search systems, information retrieval, and ranking algorithms.

• Proficiency in SQL, Python, and ML frameworks such as TensorFlow and PyTorch.

• Strong programming skills.

• Excellent communication skills, with the ability to articulate complex technical concepts to non-technical stakeholders.

🏝️ Benefits

• Competitive year-end performance bonus.

• Equity package.

• Comprehensive medical, dental, and vision coverage.

• Flexible vacation policy.

• Pet discount plans.

• Retirement plan with company match (401K).

• Opportunity to collaborate with sharp, motivated teammates on unique challenges.