Specialist Solutions Architect - Machine Learning (Manufacturing)

FEQ124R39 This position can be performed remotely. As a Specialist Solutions Architect (SSA) - Machine Learning on the Manufacturing team, you will guide customers in constructing large data solutions on Databricks that cover a wide array of machine learning applications. This customer-facing role, which assists and supports Solution Architects, requires hands-on production experience with MLFlow™ and expertise in other MLOps technology. SSAs aid customers with design and successful implementation of key workloads while aligning their technical roadmap to extend the use of the Databricks Lakehouse Platform. Reporting to the Specialist Field Engineering Manager as an in-depth expert, you will continue to develop your technical skills through mentoring, learning, and internal training programs, establishing yourself as a specialist in a particular area, whether it be machine learning, MLOps, industry knowledge, or more. The impact you will have: - Provide technical leadership to help strategic customers implement successful big data projects, ranging from feature engineering, training, tracking, registry, serving to model monitoring, all within a single platform - Architect production-level workloads, including end-to-end ML pipelines load performance testing and optimization - Become a technical expert in Databricks Machine Learning and MLOps technology - Assist Solution Architects with more complex aspects of the technical sale, including custom proof of concept content, workload size estimates, and custom architectures - Provide tutorials and training to enhance community adoption (including hackathons and conference presentations) - Contribute to the adoption of a variety of the ML offerings Databricks with customers and within the larger Databricks Community What we look for: - 5+ years of experience in a technical role with expertise in at least one of the following areas: - Data Scientist/ML Engineer: model selection, model life cycle, 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 integrates with production systems - Extensive experience in applying Data Science / ML in production to create data-driven products for addressing business problems - Experience in maintaining and extending production data systems to adapt to complex needs - Deep Specific Expertise in ML concepts, including Model Tracking, Model Serving, and other aspects of operationalizing ML pipelines in distributed data processing environments like Apache Spark, using tools such as MLflow - Production programming experience in SQL and Python, Scala, or Java - 2 years of professional experience with Big Data technologies (e.g., Spark, Hadoop, Kafka) and architectures - 2 years of customer-facing experience in a pre-sales or post-sales role - Ability to meet expectations for technical training and role-specific outcomes within 6 months of hire - Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent experience gained through work - Ability to travel up to 30% when required Benefits: - Medical, Dental, and Vision - 401(k) Plan - FSA, HSA and Commuter Benefit Plans - Equity Awards - Flexible Time Off - Paid Parental Leave - Family Planning - Fitness Reimbursement - Annual Career Development Fund - Home Office/Work Headphones Reimbursement - Employee Assistance Program (EAP) - Business Travel Accident Insurance - Mental Wellness Resources Pay Range Transparency: Databricks is dedicated to equitable and competitive compensation practices. Listening below is the salary range for this role which represents base salary range for non-commission-based roles or on-target earnings for commission-based roles. Actual compensation packages depend on several factors unique to each candidate, including but not limited to job-related skills, experience depth, relevant certifications and training, and specific work location. Based on these factors, Databricks utilizes the full width of the range. The total compensation package for this role may also include eligibility for an annual performance bonus, equity, and the benefits listed above. For more information on which range your location is in, please visit our page here.