Skip to content
AfterQueryAfterQuerySan Francisco, CA

Machine Learning Engineer

Build production ML systems for measuring, predicting, and scaling data quality for frontier AI models. Requires 3-6 years experience in applied ML or related production systems (ranking, recommendations, data quality, fraud) plus strong software engineering skills.

200k – 300k
On-site3+ YOEML Engineering

About the role

Responsibilities

  • Build ML and data systems that help measure quality across complex human data workflows
  • Develop systems for expert matching, quality prediction, and anomaly detection
  • Build evaluation infrastructure for tasks, reviewers, projects, and data deliveries
  • Turn messy real-world signals into models, metrics, and product improvements
  • Partner with engineers, domain experts, and operators to improve how high-quality data is created and reviewed
  • Own high-impact systems from early design through production deployment

Requirements

  • 3-6 YOE with relevant experience
  • Strong software engineering background with experience shipping production systems
  • Experience with applied ML, ranking, recommendations, search quality, marketplace systems, trust/safety, fraud, or data quality systems
  • Strong data intuition and ability to work with messy, ambiguous real-world signals
  • Comfort working across backend systems, data pipelines, ML models, and internal tools
  • Ability to move quickly in a high-ownership, fast-changing environment
  • Deep care for quality, precision, and customer impact

Not a Fit If

  • You want to do pure research without owning production systems
  • You only want to train models and not build product infrastructure
  • You need clean datasets and perfectly scoped problems
  • You do not want to work closely with users, operators, and domain experts

Skills

Machine LearningApplied MlRankingRecommendationsSearch QualityData Quality SystemsBackend SystemsData PipelinesProduction SystemsAnomaly DetectionQuality PredictionExpert Matching

Similar roles

ML Engineering jobs
Console

Research Engineer

ConsoleSan Francisco, CA

Research Engineer building self-improving AI agent systems at Console. Develop eval/optimization loops, fine-tune specialist models, and improve agent reasoning over enterprise context using production data to drive measurable gains in quality, latency, and reliability.

200k – 350k
On-siteML Engineering
Kepler

Machine Learning Engineer

KeplerNew York, NY

Build and own ML models, fine-tuning, evaluation harnesses, and routing for Kepler's AI agent harness in finance. Requires 5+ years production software experience and shipped ML systems focused on correctness, evals, and real-world reliability.

200k – 280k
On-site5+ YOEML Engineering
Tennr

Machine-Learning Operations Engineer

TennrNew York, NY

Founding ML Operations Engineer building scalable training, inference, and evaluation pipelines for proprietary VLMs and LLMs in healthcare. Requires 5+ years production ML infrastructure experience, strong Python/TypeScript skills, and ownership in a fast-paced startup.

200k – 230k
On-site5+ YOEML Engineering
Glean

Machine Learning Engineer, Enterprise Brain

GleanMountain View, CA

Machine Learning Engineer building the Enterprise Brain - a proactive AI system for task detection, automation, reasoning, planning and personalization using LLMs, RL, fine-tuning, and advanced ranking on top of enterprise and personal knowledge graphs. Requires 3+ years ML experience, strong production ML skills, and expertise in evaluation/benchmarking.

200k – 300k
Hybrid3+ YOEML Engineering
Snowflake

AI System Research and Development Engineer - Optimization

SnowflakeBellevue, WA

Develop and optimize GPU kernels and deep learning systems for LLM training and inference at Snowflake AI Research. Requires 5+ years in GPU/HPC optimization and strong proficiency in PyTorch, TensorFlow, JAX, and CUDA.

200k – 265k
On-site5+ YOEML Engineering