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affinity
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США
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SeniorУдалённоПолная занятость

Senior AI Engineer, AI Platform

Оценка ИИ

Отличная позиция в стабильной компании с хорошим финансированием ($120M). Прозрачная вилка зарплаты, работа с передовым стеком (LLM, Agents) и гибкий формат работы.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Роль требует глубоких знаний в современных LLM-технологиях (RAG, агенты) и 5+ лет опыта. Высокая планка ожиданий по работе с векторными БД и MLOps в условиях реального продакшена.

Анализ зарплаты

Медиана195 000 $
Рынок165 000 $ – 240 000 $
Оценка ИИ

Предлагаемая вилка $160k–$235k полностью соответствует рыночным стандартам для Senior AI ролей в США, особенно в таких хабах, как Сан-Франциско и Нью-Йорк. Верхняя граница даже несколько превышает медиану, что делает предложение очень конкурентоспособным.

Сопроводительное письмо

I am writing to express my strong interest in the Senior AI Engineer position at Affinity. With over five years of experience in software engineering and a deep focus on deploying machine learning models in production, I am excited about the opportunity to contribute to your AI Platform team. My background in architecting RAG pipelines and working with vector databases aligns perfectly with Affinity's mission to extract actionable insights from complex relationship data.

In my previous roles, I have successfully implemented LLM-powered systems, focusing on hybrid retrieval, reranking, and context window optimization. I am particularly impressed by Affinity's commitment to building a robust relationship intelligence platform and would love to bring my expertise in prompt engineering and MLOps to help scale your AI services. I am confident that my technical skills and collaborative mindset will allow me to make an immediate impact on your multi-agent systems and information retrieval challenges.

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Откликнитесь в affinity уже сейчас

Присоединяйтесь к Affinity, чтобы создавать передовые RAG-системы и определять будущее CRM для венчурного капитала!

Описание вакансии

Affinity stitches together billions of data points from massive datasets to create a powerful, accurate representation of the world's professional relationship graph. Based on this data, we offer our users the insights and visibility they need to nurture and tap into the opportunities in their team's network.

This role is part of the AI Platform team, which owns the AI services that power Affinity's industry-leading relationship intelligence platform. We extract and retrieve information from billions of structured and unstructured data points to deliver actionable insights to customers.

As a Senior AI Engineer, you will collaborate with machine learning engineers, data engineers, software engineers, and product managers to shape the future of private capital's leading CRM platform. You will design and build LLM-powered AI systems that efficiently uncover insights from compelling business interaction data – an exciting and unique opportunity within the industry.

In this role, you will:

  • Build RAG systems: Architect, prototype, and deploy RAG pipelines, combining vector search, hybrid retrieval, reranking and contextual compression techniques.
  • Build LLM powered agent systems: Contribute to design and orchestration of multi-agent LLM systems using community frameworks and custom orchestration layers.
  • Solve complex problems: Work on a variety of information extraction, information storage and information retrieval problems for both structured and unstructured data.
  • Collaborate cross-functionally: Partner with cross-functional (product, infra, data engineering, and software engineering) to build robust, high-scale systems that underlie all of our data processing and ML Operations.

Qualifications

Don’t meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every qualification. At Affinity, we are dedicated to building a diverse, inclusive, and authentic workplace, so if you’re excited about this role, but your past experience doesn’t perfectly align with the qualifications above, we encourage you to apply anyways. You may be just the right candidate for this or other roles.

Required:

  • 5+ years of experience in software engineering and/or Machine Learning experience in applying machine learning in production.
  • Hands on experience with LLM applications in production including prompt engineering and utilizing frameworks for online and offline evaluation
  • Experience with LLM assisted search, such as query understanding and augmentation, text2sql, and entity extraction
  • Experience with vector or graph databases
  • Experience with document chunking, embedding models, and context window optimization
  • Familiarity with metadata-based retrieval and re-ranking strategies
  • Hands on experiences with model evaluation metrics (e.g. perplexity, hallucination rate, factual consistency)
  • Familiarity with data security, versioning, and MLOps principles

Nice to Have:

  • Experience with enterprise AI applications with strict compliance, audit, or legal requirements
  • Experience with dataset engineering, including data curation, augmentation, and synthesis, to assist ML model improvements.
  • Experience with multi-modal search
  • Experience with graph based recommendation systems, such as graph NN.
  • Experience with developing AI applications powered by agent-based systems
  • Experience with packaging, CI/CD and pipeline automation.

Tech stack: Our ML pipeline manages multiple Python services that support various AI features, including utilizing OCR to extract information from unstructured data, serving embedding models to vectorize chunks, and ranking a list of recommendations based on relevance and user preference.

How we work:

Our culture is a key part of how we operate, as well as our hiring process:

  • We iterate quickly. As such, you must be comfortable embracing ambiguity, be able to cut through it, and deliver value to our customers.
  • We are candid, transparent, and speak our minds while simultaneously caring personally with each person we interact with.
  • We make data-driven decisions and make the best decision for the moment based on the information available.

If you’d want to learn more about our values click here.

*Work Location: San Francisco, New York, or US Remote (Affinity is registered to employ in certain U.S. states)*

For those located in San Francisco or New York, for this role we're embracing a hub-hybrid model, designed to balance flexibility with meaningful in-person collaboration. Team members within commuting distance are expected in-office 2–3 days per week, typically Tuesday through Thursday. We believe great things happen when people come together intentionally to connect, create, and build momentum as a team.

What you'll enjoy at Affinity:

  • We live our values: As owners, we take pride in everything we do. We embrace a growth mindset, engage in respectful candor, act as playmakers, and "taste the soup" by diving deep into experiences to create the best outcomes for our colleagues and clients.
  • Health Benefits: We cover your medical, dental, and vision insurance premiums with comprehensive PPO, HDHP and HMO options (in CA), and offer flexible personal & sick days to support your well-being.
  • Retirement Planning: We offer a 401(k) plan to help you plan for your future.
  • Learning & Development: We provide an annual education budget and a comprehensive L&D program.
  • Wellness Support: We reimburse monthly for things like home internet, meals, and wellness memberships/equipment to support your overall health and happiness.
  • Team Connection: Virtual team-building activities and socials to keep our team connected, because building strong relationships is key to success.

Please note that the role compensation details below reflect the base salary only and do not include any equity or benefits. This represents the salary range that Affinity believes, in good faith, at the time of this posting, that it will pay for the posted job.

A reasonable estimate of the current range is $160,000 to $235,000 USD. Within the range, individual pay depends on various factors including geographical location and review of experience, knowledge, skills, abilities of the applicant.

About Affinity

With more than 3,000 customers worldwide and backed by some of Silicon Valley's best firms, Affinity has raised $120M to empower dealmakers to find, manage, and close more deals. How? Our Relationship Intelligence platform uses the wealth of data exhaust from trillions of interactions between Investment Bankers, Venture Capitalists, Consultants, and other strategic dealmakers to deliver automated relationship insights that drive over 450,000 deals every month. We are are proud to have received Inc. and Fortune Best Workplaces awards as well as to be Great Places to Work certified for the last 5 years running. Join us on our mission to make it possible for anyone to cultivate and fully harness their network to succeed.

We use E-Verify

Our company uses E-Verify to confirm the employment eligibility of all newly hired employees. To learn more about E-Verify, including your rights and responsibilities, please visit www.dhs.gov/E-Verify.

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Навыки

  • Python
  • LLM
  • RAG
  • Vector Database
  • Graph Database
  • Prompt Engineering
  • MLOps
  • Information Retrieval
  • OCR
  • CI/CD
  • Embedding Models
  • Text-to-SQL

Возможные вопросы на собеседовании

Проверка практического опыта оптимизации RAG-систем, что является ключевой задачей роли.

Расскажите о вашем опыте оптимизации RAG-пайплайнов: какие стратегии чанкинга и методы реранжирования вы использовали для улучшения качества ответов?

Вакансия подразумевает работу с агентными системами.

С какими трудностями вы сталкивались при проектировании многоагентных LLM-систем и как вы решали проблему зацикливания или непредсказуемого поведения агентов?

Важно для оценки качества работы моделей в продакшене.

Какие метрики (например, hallucination rate, faithfulness) вы считаете наиболее критичными для оценки LLM в реальном времени и как вы их автоматизируете?

Работа с данными CRM требует понимания безопасности.

Как вы подходите к обеспечению безопасности данных и соблюдению конфиденциальности при использовании внешних LLM API?

Проверка навыков работы с неструктурированными данными, упомянутыми в стеке.

Опишите ваш опыт извлечения сущностей и структурированной информации из зашумленных текстовых данных или результатов OCR.

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affinity
Страна
США
Зарплата
160 000 $ – 235 000 $