Staff Machine Learning Engineer

Angi is a home services marketplace seeking a Staff Machine Learning Engineer to provide technical leadership across its Data Science and Machine Learning team. The role focuses on developing search, recommendation, matching, predictive, and LLM-based systems; architecting scalable MLOps practices; defining evaluation frameworks; and collaborating with engineering, infrastructure, data science, and product teams to deploy high-performing solutions.

Responsibilities:

• Model Development: Lead development of advanced machine learning and AI models to improve our marketplace algorithms (e.g. search ranking, recommendation and matching solutions). Success in these areas will impact user experience & engagement, retention, and conversion rates - critical metrics for business success
• Model Deployment and Engineering: Design and architect robust MLOps practices to ensure the seamless deployment and scalability of machine learning models, including self-hosted large language models (LLMs). This includes automating model training and post-training (fine-tuning, RLHF/preference alignment, distillation), optimizing runtime performance and inference cost of models, and owning the full MLOps lifecycle — from data pipelines and experiment tracking through CI/CD, model registry, monitoring, and rollback — to enable fast, reliable delivery of machine learning solutions into production environments
• Model Evaluation: Define and own rigorous evaluation frameworks for deep learning and ML systems — offline metrics , online experimentation (A/B testing, guardrail metrics), and LLM-specific evaluation (hallucination rate, task accuracy, human/LLM-as-judge scoring) — to ensure models meet quality and safety bars before and after deployment
• Collaboration with Cross-Functional Teams: Work closely with a strong team of engineers, ml infra team, data scientists and product managers to build scalable and high-impact machine learning systems. Collaborate on the end-to-end development process, from ideation to deployment, ensuring that data-driven solutions are seamlessly integrated into our products and services
• Innovation: Develop a long-term technical vision; propose a roadmap for team setting clear objections. Play a vital role in the design and implementation of new products and features, while also enhancing the existing product suite with innovative machine learning capabilities
• Mentorship: Guide junior team members and foster a culture of continuous learning and technical excellence. Lead and encourage knowledge sharing to enhance the team's capabilities in advanced machine learning techniques from both industry and academia

Requirements:

• You hold a Master's or Ph.D. in a quantitative field, such as Computer Science, Statistics, Mathematics, or a related discipline
• You possess 6+ years of experience in data science and machine learning, ideally within the tech industry and marketplace environments
• You have hands-on experience post-training and self-hosting open-weight LLMs (e.g., fine-tuning, quantization, serving infrastructure such as vLLM, SGLang ) rather than relying solely on third-party APIs
• You have a deep understanding of evaluation metrics across deep learning and classical ML and can design evaluation strategies that catch regressions before they reach production
• You have end-to-end fluency in the MLOps lifecycle — data versioning, feature stores, CI/CD for ML, model monitoring/observability, and retraining pipelines — not just model development
• You are knowledgeable about large-scale distributed application architecture, design, implementation, and performance tuning
• You have the ability to drive the roadmap and direction of scalable, production-quality systems end-to-end, and effectively communicate cross-functionally with Product and Engineering teams
• You have practical knowledge of advanced machine learning algorithms and deep learning to deploy for search systems, information retrieval, and ranking algorithms
• You are proficient in SQL, Python and ML frameworks (such as TensorFlow and PyTorch) with strong coding skills
• You possess excellent communication skills, with the ability to convey complex technical concepts to non-technical stakeholders