Specialist Solutions Architect
il y a 3 semaines
(FEQ125R111)
Mission
At Databricks, our core values are at the heart of everything we do; creating a culture of proactiveness and a customer-centric mindset guides us to create a unified platform that makes data science and analytics accessible to everyone. Join us in our quest to change how people work with data and make a better world
As a Specialist Solutions Architect (GenAI / ML Engineer), you will guide customers in building big data solutions on Databricks that span a large variety of machine learning and LLM use cases.You will be in a customer-facing role, working with and supporting Solution Architects, that requires hands-on production experience with MLFlow™ and expertise in other MLOps technologies.
As a go-to-expert reporting to the Specialist Field Engineering Manager, you will continue to strengthen your technical skills through mentorship, learning, and internal training programs and establish yourself in an area of speciality - whether that be machine learning, LLM, MLOps, industry expertise, or more.
The impact you will have:
Help customers through the design and successful implementation of essential workloads while aligning their technical roadmap for expanding the usage of the Databricks Data Intelligence Platform.Provide technical leadership to guide strategic customers to successful implementations on big data projectsArchitect production-level workloads, including end-to-end ML pipelines load performance testing and optimizationBecome a technical expert in Databricks Machine Learning and MLOps technologiesAssist Solution Architects with more advanced aspects of the technical sale including custom proof of concept content, estimating workload sizing, and custom architecturesProvide tutorials and training to improve community adoption (including hackathons and conference presentations)Contribute to the adoption of a variety of the ML offerings Databricks with customers as well as the larger Databricks CommunityWhat we look for:
Experience in a pre-sales or post-sales technical role with expertise in at least one of the following areas: Data Scientist / GenerativeAI / ML Engineering: model selection, model lifecycle, model scaling, AutoML, hyperparameter tuning, model serving, model monitoring, deep learning.MLOps Engineer: Build and maintain cloud infrastructure that supports the deployment of ML models and algorithms, monitors data drift, and integration with production systems. Extensive experience in applying Data Science / GenAI / ML in production to build data-driven products for solving business problems.Maintain and extend production data systems to evolve with complex customer needs.Technical expertise regarding ML concepts including Model Tracking, Model Serving and other aspects of productionizing ML pipelines in distributed data processing environments like Apache Spark, using tools like MLflowProfessional experience with Big Data technologies (Ex: Spark, Hadoop, Kafka) and production programming experience in SQL and Python, Scala, or Java.Fluent in FrenchBenefits
Private medical insurancePrivate life and disability coveragePension PlanEquity awardsEnhanced Parental LeavesFitness reimbursementAnnual career development fundWork headphones reimbursementBusiness travel accident insuranceMental wellness resourcesEmployee referral bonus-
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