Specialist Solutions Architect – Machine Learning (Public Sector)


Washington, United States


To adjust to U.S. federal authorities necessities, U.S. citizenship is required for this place. This position will be distant, nevertheless candidates should reside within the Washington, D.C., Maryland or Virginia space.

As a Specialist Options Architect (SSA) – Machine Studying on the Public Sector group, you’ll information prospects in constructing large information options on Databricks that span a big number of machine studying use circumstances. You’ll be in a customer-facing position, working with and supporting Answer Architects, that requires hands-on manufacturing expertise with MLFlow™ and experience in different MLOps applied sciences. SSAs assist prospects by means of design and profitable implementation of important workloads whereas aligning their technical roadmap for increasing the utilization of the Databricks Knowledge Intelligence Platform. As a deep go-to-expert reporting to the Specialist Subject Engineering Supervisor, you’ll proceed to strengthen your technical expertise by means of mentorship, studying, and inner coaching packages and set up your self in an space of specialty – whether or not that be machine studying, MLOps, business experience, or extra.

The influence you should have:

  • Present technical management to information strategic prospects to profitable implementations on large information initiatives, starting from characteristic engineering, coaching, monitoring, registry, serving to mannequin monitoring all inside a single platform
  • Architect manufacturing stage workloads, together with end-to-end ML pipelines load efficiency testing and optimization
  • Develop into a technical professional in Databricks Machine Studying and MLOps applied sciences
  • Help Answer Architects with extra superior points of the technical sale together with customized proof of idea content material, estimating workload sizing, and customized architectures
  • Present tutorials and coaching to enhance neighborhood adoption (together with hackathons and convention displays)
  • Contribute to adoption of a wide range of the ML choices Databricks with prospects in addition to the bigger Databricks Group

What we search for:

  • Should be eligible and keen to be processed for a U.S. Authorities clearance
  • [Preferred] DoD Secret or High Secret Clearance
  • 5+ years expertise in a technical position with experience in no less than one of many following:
    • Knowledge Scientist/ML Engineer: mannequin choice, mannequin lifecycle, mannequin scaling, AutoML, hyperparameter tuning, mannequin serving, mannequin monitoring, deep studying
    • MLOps Engineer: Construct and keep cloud infrastructure that helps the deployment of ML fashions and algorithms, displays information drift, integration with manufacturing programs
  • Intensive expertise in making use of Knowledge Science / ML in manufacturing to construct data-driven merchandise for fixing enterprise issues
  • Expertise sustaining and increasing manufacturing information programs to evolve with complicated wants
  • Deep Specialty Experience relating to ML ideas together with Mannequin Monitoring, Mannequin Serving and different points of productionizing ML pipelines in distributed information processing environments like Apache Spark, utilizing instruments like MLflow
  • Manufacturing programming expertise in SQL and Python, Scala, or Java
  • 2 years skilled expertise with Massive Knowledge applied sciences (e.g. Spark, Hadoop, Kafka) and architectures
  • 2 years customer-facing expertise in a pre-sales or post-sales position
  • Can meet expectations for technical coaching and role-specific outcomes inside 6 months of rent
  • Bachelor’s diploma in Pc Science, Data Programs, Engineering, or equal expertise by means of work expertise
  • Capacity to journey as much as 30% when wanted in and across the DMV space


  • Medical, Dental, and Imaginative and prescient
  • 401(ok) Plan
  • FSA, HSA and Commuter Profit Plans
  • Fairness Awards
  • Versatile Time Off
  • Paid Parental Depart
  • Household Planning
  • Health Reimbursement
  • Annual Profession Growth Fund
  • Residence Workplace/Work Headphones Reimbursement
  • Worker Help Program (EAP) 
  • Enterprise Journey Accident Insurance coverage
  • Psychological Wellness Sources

Pay Vary Transparency

Databricks is dedicated to honest and equitable compensation practices. The pay vary(s) for this position is listed under and represents base wage vary for non-commissionable roles or on-target earnings for commissionable roles.  Precise compensation packages are based mostly on a number of elements which are distinctive to every candidate, together with however not restricted to job-related expertise, depth of expertise, related certifications and coaching, and particular work location. Based mostly on the elements above, Databricks makes use of the total width of the vary. The full compensation bundle for this place may embrace eligibility for annual efficiency bonus, fairness, and the advantages listed above. For extra info relating to which vary your location is in go to our web page here.


Zone 2 Pay Vary
$139,700$247,300 USD

About Databricks

Databricks is the info and AI firm. Greater than 10,000 organizations worldwide — together with Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — depend on the Databricks Knowledge Intelligence Platform to unify and democratize information, analytics and AI. Databricks is headquartered in San Francisco, with workplaces across the globe and was based by the unique creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To be taught extra, observe Databricks on TwitterLinkedIn and Facebook.

Our Dedication to Variety and Inclusion

At Databricks, we’re dedicated to fostering a various and inclusive tradition the place everybody can excel. We take nice care to make sure that our hiring practices are inclusive and meet equal employment alternative requirements. People searching for employment at Databricks are thought of with out regard to age, colour, incapacity, ethnicity, household or marital standing, gender identification or expression, language, nationwide origin, bodily and psychological capability, political affiliation, race, faith, sexual orientation, socio-economic standing, veteran standing, and different protected traits.



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