Note: The job is a remote job and is open to candidates in USA. EY is seeking a Manager to lead client-facing AI and machine learning engineering engagements focused on Databricks. The role involves designing and delivering production-grade data, machine learning, generative AI, and agentic AI solutions, while guiding teams and helping clients realize value from the platform.
Responsibilities
- Leading AI workstreams from solution design through production deployment and ongoing optimization, focusing on the Databricks platform
- Leading teams building data engineering pipelines, AI solutions (machine learning, generative AI, and agentic AI), and the pipelines that support AI solutions on Databricks
- Continuously improving processes by identifying innovative solutions through research and analysis
- Managing multidisciplinary teams to deliver complex AI engineering initiatives, with accountability for quality, responsible deployment, and results
- Engaging actively with clients, participating in daily working sessions, and leading workstreams from planning through execution to closure
- Designing, building, and governing domain ontologies and semantic models that define business concepts, relationships, and rules for AI solutions, knowledge graphs, and enterprise data products
- Applying a product-centric development approach by partnering with product, business, data science, and engineering stakeholders to define user needs, prioritize reusable capabilities, and iteratively deliver measurable outcomes across the product lifecycle
- Identifying opportunities for additional services and managing engagement economics
Skills
- A Bachelor's degree required (4-year degree)
- 6-10 years of relevant experience of full-time working experience in AI, Data Science, and/or Machine Learning
- 2-4 years of experience directly managing technical teams
- 3-4 years of experience building and deploying production AI/ML solutions on the Databricks platform, including use of Agent Bricks, Model Serving, or Lakeflow Jobs
- Databricks Certification with a minimum of 1 professional and 1 associate certification that includes a combination of Data Engineer Associate or Professional, Machine Learning Associate or Professional, Generative AI Engineer Associate, and/or Context Engineering Associate
- Strong skills in Python, PySpark, and/or Scala
- Ability lead, collaborate, and communicate effectively with diverse, hybrid and global teams
- Experience designing, building, and maintaining high-impact, high-value production AI/ML solutions on a major cloud platform, using Databricks
- Delivered models or agents to production on Databricks, with tracking, evaluation, and monitoring
- Proficient in foundation models, generative AI, and agentic AI frameworks (e.g., Retrieval Augmented Generation (RAG)) and experienced with ML packages like scikit-learn and PyTorch, using Databricks tools including Agent Bricks, AI Search, Foundation Model APIs, and Unity Gateway
- Experience withnatural language processing and deep learning
- Extensive experience in DevOps tools (Git, Azure DevOps), AI-driven SDLC, and CI/CD pipelines for developing, deploying, and scaling analytical solutions on Databricks, for example with Databricks Git folders, Declarative Automation Bundles, and the Databricks CLI and SDKs
- Experience with MLOps, LLMOps, and AgentOps and ML workflows on Databricks, including data ingestion, transformation, and evaluation, for example with MLflow, Models in Unity Catalog, and Model Serving
- Experience with model retraining and feedback loop methodologies on Databricks, for example with Lakeflow Jobs and Databricks Feature Store
- Experience with model and solution evaluation, observability, monitoring, and reporting on Databricks, including MLflow evaluation and tracing, and data quality monitoring
- Understanding of data structures, data modeling, software engineering, and Responsible AI practices
- Experience designing, implementing, validating, and maintaining ontologies, taxonomies, knowledge graphs, or semantic data models in collaboration with domain experts
- Experience with product-centric development, including translating customer and business needs into product requirements, roadmaps, iterative releases, and measurable adoption or performance outcomes
- Strong foundation in mathematics, statistics, and operations research, with proficiency in data manipulation tools (SQL, Pandas, Spark) and deep learning techniques, using Databricks tools including Databricks SQL and Delta Lake
- Excellent communication skills for conveying findings and recommendations
- Skills in Technical Design Optimization
- Strong relationship-building skills
- Demonstrated client trust and value
- Digital fluency and emotional agility
- Commercial acumen and negotiation skills
- Proven ability to lead teams and manage change
- A deep understanding of and ability to teach concepts, tools, features, functions, and benefits of different approaches to apply them
- Master's degree Computer Science, Mathematics, Physical Sciences, or other quantitative field
- Databricks Solution Architect Champion Badge preferred
- Experience working with diverse teams to deliver complex solutions
- Experience fine-tuning Generative AI models on Databricks, including with AI Runtime (serverless GPU)
- Experience in managing complex projects with multiple stakeholders
- A strong understanding of industry trends and emerging technologies
- Skills in data visualization and storytelling with data
- Experience with image processing techniques and/or speech and audio processing and analysis
- Databricks Certifications in the Data & AI domain, including Data Engineer Associate or Professional, Machine Learning Associate or Professional, Generative AI Engineer Associate, and/or Context Engineering Associate
- Experience building data and AI applications on Databricks, including with Databricks Apps or Lakebase Postgres
Benefits
- Medical and dental coverage
- Pension and 401(k) plans
- A wide range of paid time off options
Company Overview
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