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Today

Machine Learning Engineer, GAI Search Platform

ServiceNow Mountain View, CA

Mountain View, CA

Today

$140k - $217k/yr Full time Agentic Ai AI Ai Ml

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Job Description

ServiceNow’s GenAI Search Platform team is hiring Machine Learning Engineers to advance enterprise search-based question answering. The work combines traditional machine learning with generative AI and LLMs, with a focus on building LLM-enabled search capabilities and establishing systematic evaluation for ranking and summarization grounded in heterogeneous knowledge sources.

Responsibilities

Drive development of the search platform using LLM-enabled generative AI features in a fast-paced environment, supporting product teams as they build new applications and features quickly.
Ship prototypes to customers at scale, evaluate and iterate on ranking improvements in a systematic manner, and enforce guarantees related to quality, security, privacy, and scalability.
Create systematic evaluation metrics and methodologies for search models, using LLMs to address enterprise-specific challenges such as security and privacy.
Collaborate with ranking, product, design, infrastructure, and data science teams to develop next-generation agentic search capabilities with an emphasis on performance and enterprise readiness.
Partner with product, user experience, customer success, and engineering teams to identify, define, and build solutions.

Required Qualifications

3+ years of engineering experience.
First-hand experience relevant to search platforms, including traditional information retrieval, search ranking and relevance, recommendation systems, or question answering systems.
Background in text processing, information retrieval, natural language understanding, or machine learning.
Strong interest in helping product and ranking teams move faster and scale solutions effectively while maintaining customer impact and success as priorities.

Technologies

LLMs (large language models)
Natural language understanding
Retrieval augmented generation (RAG)

Nice to Have

Experience with, or interest in learning, large language models, retrieval augmented generation (RAG), and agents.
Experience with Python, including contributing to mature Python libraries or platform code, including open-source repositories.
Experience in Golang (not required).

Compensation and Benefits

Base pay: $139,700 - $216,500 per year.
Equity (when applicable), variable or incentive compensation, and benefits.
Health plans, including flexible spending accounts.
401(k) plan with company match.
ESPP.
Matching donations.
Flexible time away plan.
Family leave programs.

Work Location and Work Persona

The role is based in Mountain View, CA and is onsite.

ServiceNow assigns work personas (flexible, remote, or required in office) based on the nature of the work and the assigned work location. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.

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4d ago

Data Scientist, Research, Search Platforms

Google Mountain View, CA

Mountain View, CA

4d ago

$174k - $253k/yr Full time Big Data Data Data Analysis

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Job Description

The Search Platform Data Science team at Google focuses on understanding, measuring, and improving Google Search systems, with an emphasis on the end-to-end user experience. In this role, you will work at the intersection of Advanced Causal Inference, Product Analytics, and Machine Learning, helping teams make measurement and decision-making stronger across complex, real-world environments.

You will be responsible for methodological innovation and analytics execution, from defining how to measure user experience to building scalable pipelines and translating results into recommendations. The work spans topics including Experimentation, Reliability, Velocity, Latency, Capacity, Content, Regulation, and Antiscraper.

Role focus

Understand and improve Search systems by combining measurement approaches with analytical rigor across the user journey.
Pioneer methodological innovations to capture and improve end-to-end user experience, including scaling User-Perceived Reliability metrics.
Apply advanced causal inference techniques to measure the impact of user friction on long-term retention.
Prototype and apply creative workarounds when clean data is unavailable, including using LLMs to synthesize ground-truth labels.
Drive analytical excellence across the organization by authoring frameworks and best practices to educate the broader Data Science community.

Responsibilities

Extract strategic insights from large, complex datasets that include client-side and server-side logs, tackling intricate, non-routine analytical problems to optimize the user experience for AIM and AIO products.
Lead end-to-end analyses, including data ingestion, requirements specification, processing, modeling, ongoing deliverables, and professional presentations.
Build and iteratively refine analysis pipelines to provide insights at scale.
Collaborate cross-functionally with engineers and multiple teams (including Platform and Product) to identify opportunities, design improvements, and assess impact for AI products.
Develop strategic business recommendations, such as growth headroom estimates, cost-benefit assessments of engineering optimizations, and marketing campaign effectiveness, and present findings to multiple leadership levels.

Requirements

Master’s degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field.
Minimum experience: 5 years using analytics to solve product or business problems, including coding (Python, R, SQL) and querying databases or conducting statistical analysis; alternatively, 3 years with a PhD.
Ability to take open-ended problems, define them more precisely over time, and work toward solutions.

Preferred qualifications

8 years using analytics to solve product or business problems, including coding (Python, R, SQL) and querying databases or conducting statistical analysis; alternatively, 6 years with a PhD.

Technologies

Python
R
SQL
LLMs

Location and compensation

Location: Mountain View, CA (onsite)
Salary: USD 174,000 - 253,000 per year
Bonus target: 15%
Additional compensation: equity
Benefits: benefits

Work location preference

Applicants can share a preferred working location from: Mountain View, CA, USA; Cambridge, MA, USA

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Search Platforms Data Jobs

Machine Learning Engineer, GAI Search Platform

Data Scientist, Research, Search Platforms

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