A

Accenture

Advises businesses and runs their technology

Databricks Artificial Intelligence Machine Learning Engineer

Data EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • At least 2 years of experience applying data-driven approaches to business scenarios, including the design, deployment, and operation of advanced analytics and machine learning solutions.
  • At least 1 year within that experience working with Databricks in Generative AI and/or Agentic AI, building scalable AI/ML solutions such as retrieval-augmented generation, tool-using agents, evaluation, and monitoring.
  • Hands-on experience delivering AI/ML and Generative AI solutions on Databricks Lakehouse AI or Databricks ML in production.
  • Practical Databricks MLOps skills, including MLflow tracking and Model Registry, MLflow Tracing, Workflows/Jobs orchestration, Repos, and Asset Bundles for packaging and deploying across environments.
  • Familiarity with Databricks Generative AI capabilities, including Mosaic AI Vector Search for retrieval-augmented generation, Agent Framework, AI Gateway, and AI/BI Genie for governed natural-language Q&A or natural-language-to-SQL aligned with Unity Catalog.
  • Experience with Python-based AI frameworks such as LangChain, LangGraph, CrewAI, AutoGen, LlamaIndex, or Hugging Face Transformers, or similar frameworks.
  • Experience delivering analytical projects on Azure, AWS, or Google Cloud Platform; ideally with Databricks as the execution layer. Examples include Azure OpenAI, AWS Bedrock, or Vertex AI used alongside Databricks for Generative AI workloads.
  • Solid understanding of machine learning and data science techniques, including clustering, regression, classification, and forecasting.
  • Solid understanding of neural networks and hyperparameter optimization.
  • Solid understanding of natural language processing, large language models, retrieval concepts, and evaluation of Generative AI systems.
  • Ability to translate complex business requirements into robust, data-driven solutions and production-ready architecture.
  • Professional working proficiency in English.
  • Willingness and ability to travel to client locations, mostly across Europe and beyond, for short or long-term assignments.

Responsibilities

  • Design and implement scalable end-to-end data pipelines using Databricks for batch and streaming, including extract, transform, load and extract, load, transform processes and orchestration patterns such as Delta Live Tables.
  • Develop and maintain data models using Lakehouse and Medallion architecture, including Bronze, Silver, and Gold layers.
  • Build robust data transformations using PySpark, Spark SQL, and Delta Lake.
  • Integrate diverse cloud and enterprise data sources into unified, high-quality, analytics-ready datasets.
  • Collaborate with architects, analysts, and data scientists to deliver production-grade data products.
  • Implement DevOps and DataOps practices, including Git-based version control, continuous integration and continuous delivery pipelines, and testing of data workflows.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

Recently Posted Jobs

Explore more opportunities at Accenture

See more jobs