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Salary
$80k – $193k per year (Estimated)
Location
In office (Paris)
Seniority
Architect
Overview
Company
Impact
Profile match
Databricks is an American software company founded in 2013 by the original creators of Apache Spark, Delta Lake and MLflow at the University of California, Berkeley. Its data intelligence platform unifies data engineering, warehousing, governance, analytics and machine learning on a lakehouse architecture that stores open table formats in a customer's own cloud object storage. Headquartered in San Francisco and available on AWS, Azure and Google Cloud, the platform is used by tens of thousands of organisations to build pipelines, dashboards and production AI applications.

At Databricks, we are passionate about enabling data teams to solve the world's toughest problems. Our customers leverage the Databricks Data Intelligence Platform to power their mission critical Data and AI applications to improve how their organisations leverage data and insights to make better decisions, faster. Customers rely on Databricks for the full range of data workloads, including data engineering, ETL, near real-time streaming, machine learning, SQL analytics, and advanced analytics. 

As a Product Specialist - Gen AI (Sr. Specialist Solutions Architect) you will be a deep technical expert in Gen AI and Machine Learning  and in how customers can be successful with these use-cases in the Lakehouse paradigm. You will work closely with both Product Management and the EMEA Field Engineering and Sales teams to act as the technical bridge between these critical organisations to help make the Data Intelligence Platform vision a reality for our customers. You will provide thought leadership on best practices around how to build and deploy agentic AI systems with Databricks. You will work closely with the Databricks Product Management team to drive adoption of Gen AI features and ensure a consistent product vision for the EMEA technical field. You will work closely with specific accounts on our most challenging Gen AI use-cases around reinforcement learning and fine-tuning in particular. 

You will report directly to the Sr. Director Product Specialists Databricks Field Engineering and can be located in Paris or Amsterdam. Databricks Field Engineering works with our current and future customers to grow adoption, win technical validations and advise customers on Gen AI best practices. The Product Specialist -  Gen AI owns the enablement and escalations within the EMEA Field Engineering team around relevant features.

The impact you will have:

  • Deliver thought leadership in Gen AI best practices for the Databricks Data Intelligence Platform in the form of blogs, webinars, how to guides and technical know-how to the EMEA technical community and beyond.
  • Working with sales and FE leaders drive adoption of Gen AI across EMEA
  • Provide a strong, informed, and data-driven perspective in conversations with the Product and Engineering teams to influence our product strategy and priorities in how customers can and should bring Databricks into their Data strategies. 
  • Provide guidance and oversight for large-scale enterprise Gen AI competitive scenarios, serving as a trusted technical advisor to senior tech leads and executives
  • Work closely with key customers on specific Gen AI use-cases helping translate research innovations into production grade AI applications

What we look for:

  • Experience designing and delivering production-grade Generative AI and Deep Learning solutions in customer or enterprise environments
  • Strong hands-on experience with LLMs and modern Deep Learning: Transformer architectures, PyTorch, and distributed/multi-GPU training
  • Hands-on experience taking LLM post-training beyond fine-tuning: SFT plus reinforcement learning-based methods - reward modeling, RLHF/RLAIF, or policy optimization (e.g., PPO, GRPO) - applied to steer models toward specific behaviors and quality criteria
  • Ability to advise customers on GenAI and Deep Learning architectures, translate requirements into technical solutions, and anticipate and remove implementation blockers
  • Strong hands-on experience with Python, SQL, Apache Spark, cloud platforms, and Lakehouse architectures; excellent communication skills and customer-facing/pre-sales experience are highly desirable.
  • Excellent communication skills; both written and verbal
  • Experience in pre-sales selling highly desired

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide - including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 - rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

Our Commitment to Diversity and Inclusion

At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.

Compliance

If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.

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