Specialist Solutions Architect - Machine Learning (Healthcare & Life Sciences)

As a Specialist Solutions Architect (SSA) - Machine Learning on the Healthcare & Life Sciences team, you will guide customers in constructing big data solutions on Databricks that deal with a wide range of machine learning applications. Your role will involve direct engagement with customers, collaborating with and assisting Solution Architects, and requires hands-on production experience with MLFlow™ and expertise in other MLOps technologies. SSAs support customers during the design and successful implementation of critical workloads while coordinating their technical roadmap for broadening 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 via mentorship, learning, and internal training programs and establish your mastery in a specific field - be it machine learning, MLOps, industry knowledge, or more. The impact you will have: - Give technical guidance to direct strategic customers towards successful implementations on big data projects, from feature development, training, tracking, registry, serving to model monitoring in a single platform. - Architect production-level workloads, comprising end-to-end ML pipeline load performance testing and optimization. - Become a technical authority in Databricks Machine Learning and MLOps technologies. - Assist Solution Architects with more advanced aspects of the technical sale, including custom proof of concept content, estimating workload sizing, and custom architectures. - Supply tutorials and training to improve community adoption (including hackathons and conference presentations). - Contribute to the adoption of various Databricks ML offerings by customers and the broader Databricks Community. Qualifications we look for: - You must be eligible and willing to process a U.S. Government clearance. - [Preferred] DoD Secret or Top Secret Clearance. - 5+ years experience in a technical role with expertise in at least one of the following: - Data Scientist/ML Engineer: model selection, model lifecycle, model scaling, AutoML, hyperparameter tuning, model serving, model monitoring, deep learning. - MLOps Engineer: building and maintaining cloud infrastructure that supports deploying ML models and algorithms, monitoring data drift, integration with production systems. - Extensive experience in employing Data Science / ML in production to create data-driven products for solving business issues. - Experience in maintaining and extending production data systems to adapt to complex requirements. - Profound Specialty Expertise in ML concepts including Model Tracking, Model Serving, and other aspects of operationalizing ML pipelines in distributed data environments like Apache Spark, using tools like MLflow. - Programming experience in a production setting in SQL and Python, Scala, or Java. - 2 years professional experience with Big Data technologies (e.g. Spark, Hadoop, Kafka) and architectures. - 2 years customer-facing experience in a pre-sales or post-sales role. - Capable of achieving expectations for technical training and role-specific outcomes within 6 months of hiring. - Bachelor's degree in Computer Science, Information Systems, Engineering, or equivalent experience gained through work. - Ability to travel up to 30% when necessary, within and around the DMV area. 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 committed to fair and equitable compensation practices. The pay range(s) for this role is provided below, representing the base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are influenced by several factors pertinent to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on these elements, Databricks utilizes the full width of the range. The total compensation package for this position may also include eligibility for an annual performance bonus, equity, and the benefits mentioned above. For more information regarding which range your location is in, visit our page here.