10 hours ago
Base Salary
$200k - $250k/yr
Responsibilities
- Develop advanced machine learning and AI models for search ranking, recommendations, matching, and marketplace optimization.
- Design and own MLOps practices covering training, post-training, deployment, model registries, monitoring, rollback, and production scalability.
- Post-train and self-host open-weight LLMs using techniques such as fine-tuning, quantization, preference alignment, and distillation.
- Optimize model runtime performance, inference costs, and low-latency serving.
- Build evaluation frameworks covering offline metrics, online experimentation, guardrail metrics, and LLM-specific quality measures.
- Collaborate with platform engineers, ML infrastructure, data scientists, and product managers throughout the product development lifecycle.
- Help define the team’s technical vision and roadmap for scalable production-quality systems.
- Mentor junior team members and promote knowledge sharing and technical excellence.
Requirements
- Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
- At least 4 years of experience in data science and machine learning, ideally in technology or marketplace environments.
- Hands-on experience post-training and self-hosting open-weight LLMs, including fine-tuning, quantization, and serving infrastructure such as vLLM or SGLang.
- Deep understanding of evaluation metrics for deep learning and classical machine learning systems.
- End-to-end experience with MLOps, including data versioning, feature stores, ML CI/CD, model monitoring and observability, and retraining pipelines.
- Knowledge of large-scale distributed application architecture, implementation, and performance tuning.
- Ability to drive the roadmap and direction of scalable production systems and communicate effectively with product and engineering stakeholders.
- Practical knowledge of machine learning and deep learning for search, information retrieval, and ranking systems.
- Proficiency in SQL, Python, TensorFlow, and PyTorch.
- Strong communication skills for explaining complex technical concepts to non-technical stakeholders.
Benefits
- Competitive year-end performance bonus and equity package.
- Full medical, dental, and vision coverage.
- Flexible vacation policy.
- Pet discount plans.
- Retirement plan with company match through a 401(k).
- Opportunity to work with motivated teammates on marketplace and machine learning challenges.
Categories
About Angi
Angi operates a marketplace that connects homeowners with local home service professionals through its website and mobile apps. It generates revenue by selling leads and advertising/subscription packages to pros and by facilitating online booking. Founded in 1995 and headquartered in Denver, it is a public company on Nasdaq and spans the U.S., Canada, and Europe, with a network of over 200,000 service professionals.