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databricks
Страна
США
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180 000 $ – 247 500 $
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Specialist Solutions Architect - AI & ML (Communications, Media, Entertainment & Games)

Оценка ИИ

Исключительная вакансия от лидера рынка ИИ с очень конкурентной заработной платой и возможностью работать с передовыми технологиями (GenAI, LLMs). Databricks — престижный работодатель с сильной инженерной культурой.


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Сложность вакансии

ЛегкоСложно
Оценка ИИ

Высокая сложность обусловлена требованием глубоких знаний в области GenAI, MLOps и архитектуры облачных решений, а также необходимостью иметь более 5 лет опыта и магистерскую степень. Роль совмещает в себе глубокую техническую экспертизу и навыки пресейла/консалтинга.

Анализ зарплаты

Медиана210 000 $
Рынок175 000 $ – 260 000 $
Оценка ИИ

Предлагаемый диапазон $180k – $247k полностью соответствует и даже несколько превышает рыночные стандарты для Senior/Specialist Solutions Architect в США, где медиана составляет около $210k. Верхняя граница диапазона отражает высокую ценность специалистов по Generative AI.

Сопроводительное письмо

I am writing to express my strong interest in the Specialist Solutions Architect - AI & ML position at Databricks. With over five years of experience in machine learning engineering and a deep focus on productionizing AI workloads, I have closely followed Databricks' evolution from the creators of Apache Spark to the pioneers of the Data Intelligence Platform. My background in architecting RAG systems and MLOps pipelines aligns perfectly with your mission to help customers build production-grade GenAI applications.

In my previous roles, I have successfully bridged the gap between complex technical architectures and business value, a skill I look forward to bringing to the Communications, Media, and Entertainment sector at Databricks. I am particularly excited about the opportunity to leverage MLflow and Unity Catalog to solve large-scale challenges for Fortune 500 clients. I am confident that my technical expertise in LLM orchestration and my passion for customer success will make me a valuable asset to your Field Engineering team.

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Описание вакансии

FEQ227R247

Mission

As a Specialist Solutions Architect (SSA) - ML & AI Engineer, you will be the trusted technical ML & AI expert to both Databricks customers and the Field Engineering organization. You will work with Solution Architects to guide customers in architecting production-grade ML & AI applications on Databricks, while aligning their technical roadmap with the continually evolving Databricks Data Intelligence Platform. You will continue to strengthen your technical skills through applying cutting edge technologies in GenAI, MLOps, and ML more broadly, expanding your impact through mentorship, and establishing yourself as an AI thought leader.

The impact you will have:

  • Architect production level ML & AI workloads for customers using our unified platform, including agents, end-to-end ML pipelines, training/inference optimization, integration with cloud-native services, MLOps, etc.
  • Serve as trusted practitioner for enterprise GenAI solutions, including RAG architectures, agentic systems (tool-calling agents, multi-agent orchestration, guardrails), natural language querying of structured data, AI evaluation and observability, and monitoring systems
  • Build, scale, and optimize customer AI workloads and apply best in class MLOps to productionize these workloads across a variety of domains
  • Provide advanced technical support to Solution Architects during the technical sale ranging from feature engineering, training, tracking, serving to model monitoring all within a single platform, as well as participating in the larger ML SME community in Databricks
  • Collaborate cross-functionally with the product and engineering teams to represent the voice of the customer, define priorities and influence the product roadmap, helping with the adoption of Databricks’ AI offerings

What we look for:

  • 5+ years of hands-on industry ML experience in at least one of the following:
  • ML Engineer: Build and maintain production-grade cloud (AWS/Azure/GCP) infrastructure that supports the deployment of ML applications, including drift monitoring.
  • AI Engineer: Experience with the latest techniques in LLMs & agentic systems including vector databases, fine-tuning LLMs, AI guardrail systems, and deploying LLMs with tools such as HuggingFace, Langchain, and OpenAI
  • Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
  • Experience communicating and/or teaching technical concepts to non-technical and technical audiences alike
  • Passion for collaboration, life-long learning, and driving business value through ML & AI
  • [Preferred] 2+ years customer-facing experience in a pre-sales or post-sales role
  • Can meet expectations for technical training and role-specific outcomes within 3 months of hire
  • This role can be remote, but we prefer that you be located in the job listing area and can travel up to 30% when needed

Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.  Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

Local Pay Range

$180,000—$247,500 USD

About Databricks

Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on TwitterLinkedIn and Facebook.

BenefitsAt Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region, please visit https://www.mybenefitsnow.com/databricks

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

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Навыки

  • AWS
  • Azure
  • Python
  • GCP
  • Machine Learning
  • LLM
  • MLOps
  • RAG
  • Apache Spark
  • Generative AI
  • MLflow
  • LangChain
  • Vector Databases
  • Hugging Face

Возможные вопросы на собеседовании

Проверка практического опыта работы с современными ИИ-архитектурами, которые являются ключевыми для этой роли.

Расскажите о вашем опыте проектирования и внедрения RAG-систем (Retrieval-Augmented Generation) в продакшн. С какими основными проблемами вы столкнулись?

Databricks делает упор на полный жизненный цикл ML. Вопрос проверяет знание инструментов компании и методологии MLOps.

Как бы вы организовали процесс мониторинга дрейфа данных и моделей для LLM, используя инструменты экосистемы Databricks, такие как MLflow?

Роль подразумевает работу с клиентами и помощь в продажах. Важно уметь объяснять сложные вещи просто.

Как бы вы объяснили техническому директору (CTO) клиента преимущества перехода с разрозненных ML-инструментов на единую платформу Data Intelligence Platform?

Проверка навыков оптимизации, что критично для высоконагруженных систем в медиа и гейминге.

Какие стратегии оптимизации инференса (вывода) моделей вы применяли для снижения задержек и стоимости эксплуатации в облачных средах?

Проверка навыков проектирования сложных систем.

Опишите архитектуру агентской системы (agentic system), которую вы разрабатывали. Как вы решали вопросы оркестрации и безопасности (guardrails)?

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databricks
Страна
США
Зарплата
180 000 $ – 247 500 $