15 часов назад
Solutions Architect, Customer Success (AI Observability)
160 000 - 200 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Solutions Architect, Customer Success (AI Observability): Driving customer onboarding, integrations, and adoption of Fiddler’s AI observability platform with an accent on ML/LLM systems, model transparency, and production-scale monitoring. Focus on designing secure data pipelines, connecting platforms such as Snowflake, Airflow, MLflow, S3, and Kafka, and translating complex technical challenges into measurable customer outcomes.
Location: US - Remote. For candidates in the San Francisco Bay Area, the role is hybrid and requires working from the Palo Alto office 3 days a week.
Salary: $160,000–$200,000 for US locations; $190,000–$230,000 for San Francisco, New York City, and Seattle, plus equity.
Company
builds an AI Observability platform that helps organizations monitor, evaluate, secure, analyze, and improve machine learning and generative AI systems.
What you will do
- Architect and implement customer onboarding solutions in partnership with Delivery Managers.
- Guide data science and ML engineering teams through AI observability adoption and help them achieve measurable outcomes.
- Lead technical engagements, roadmap discussions, QBRs, status syncs, and escalation management.
- Build custom integrations with data ecosystems and workflow tools such as Snowflake, Airflow, MLflow, S3, and Kafka.
- Develop reusable integration patterns across data platforms, workflow tools, and ML infrastructure.
- Identify expansion opportunities through advanced observability use cases, integrations, and model governance.
Requirements
- Bachelor’s degree in Computer Science with an AI/ML focus, Statistics, Mathematics, or a related field, plus 5–7+ years of professional experience.
- 2+ years of hands-on experience deploying, monitoring, or maintaining machine learning models in production.
- Strong communication, presentation, storytelling, organizational, and project management skills.
- Understanding of data science, model interpretability, explainability, and the ML/DS lifecycle.
- Working knowledge of data and workflow tools including Hadoop, MongoDB, Snowflake, BigQuery, Spark, Kafka, Kinesis, RabbitMQ, Airflow, MLflow, Luigi, Kubeflow, or Argo.
- Experience with TensorFlow, PyTorch, or Scikit-learn, plus Kubernetes and AWS, Azure, or GCP.
Nice to have
- Familiarity with generative AI, large language models, RAG architectures, and agent-based systems.
- Experience with batch and real-time scoring through REST APIs.
- Thought leadership and the ability to inspire customers and peers through technical credibility.
Culture & Benefits
- Remote-first collaboration with frequent communication, peer learning, knowledge sharing, and collective problem solving.
- Competitive pay and equity.
- Unlimited PTO, premium health, dental, and vision coverage with 100% employee premium coverage.
- 401(k), monthly fitness reimbursement, and paid parental leave.
- Palo Alto office benefits include an annual Caltrain pass, Fastrak reimbursement, in-office massages, and lunch Monday through Thursday.
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