Senior Global Data AI Specialist

Technology, Data & Digital · Data, AI & Analytics · Data Science · Machine Learning · Artificial Intelligence

In short

ABB seeks a hands-on AI/ML Engineer for a Senior Global Data AI Specialist role, building AI solutions from idea to production. This hybrid position requires expertise in Azure AI/ML, Snowflake, GenAI, and MLOps, and involves working with business stakeholders to develop predictive models, LLMs, AI agents, and other AI applications.

Responsibilities

Work with business stakeholders and Data Analysts to clarify needs, requirements, expected outcomes, success measures, data and context requirements, risks and ownership.
Decide which approach fits each business problem best: AI/ML, GenAI, analytics, automation or a conventional solution.
Design scalable solutions that follow enterprise architecture, security and governance standards.
Develop, validate and deploy production-ready AI/ML solutions using Python, SQL, Azure Machine Learning, Microsoft Foundry and other approved technologies.
Build ML and GenAI applications, including predictive models, RAG, embeddings, vector search, prompt/context engineering, AI agents, APIs, orchestration, retrieval and enterprise data integrations.
Build and integrate LLM-based solutions and conversational agents using Microsoft Foundry, Azure OpenAI and, where appropriate, Copilot Studio and Power Platform.
Use enterprise data from SAP and Salesforce to build predictive models, GenAI applications and AI agents that deliver measurable business value.
Build secure, reliable data ingestion and processing from Snowflake and other enterprise sources, with attention to data quality, lineage, access control and cost efficiency.
Apply Snowflake AI/ML capabilities, including Snowpark ML, Cortex AI, Cortex Search and AI Functions.
Develop reusable components and automated pipelines for data preparation, feature engineering, training, inference, evaluation, testing, deployment and retraining, using CI/CD and version control.
Evaluate model accuracy, explainability, grounding, agent behaviour, safety, business value, performance, reliability and cost.
Set up and run MLOps/AIOps practices: monitoring, drift detection, cost monitoring, root-cause analysis, retraining and continuous improvement.
Contribute to production readiness, operational handover, incident and problem analysis, monitoring design and reliable day-to-day operations.
Apply Responsible AI, information security, privacy, compliance, identity and access management, secrets management and other ABB requirements within your solution scope.
Own your deliverables end to end. Estimate effort, manage priorities, report progress and risks, and work independently within the agreed architecture and platform guardrails.
Work closely with Data Analysts, Data Scientists, Snowflake Developers, Data Engineers, Power BI/Fabric Developers, platform specialists and domain experts.
Document solution logic, assumptions, limitations, evaluation results and operational requirements.
Contribute reusable assets, engineering practices, knowledge sharing and mentoring.

Requirements

Master's degree in Computer Science, Data Science, Statistics, Applied Mathematics, Engineering or a related technical field, or equivalent practical experience.
4–6 years of hands-on experience in Data Science, AI/ML Engineering, analytics engineering or related roles, including taking AI/ML solutions to production.
Experience delivering AI/ML solutions end to end: business requirements, data preparation, development, validation, deployment and monitoring.
Practical Python and SQL skills for data preparation, model development, API integration, testing and implementation.
Hands-on experience with Azure Machine Learning and Microsoft Foundry: pipelines, compute, environments, model deployment, endpoints, agents and evaluation.
Strong understanding of GenAI patterns: LLMs, RAG, embeddings, vector search, prompt/context engineering, agent design and evaluation.
Working knowledge of ML and statistics: supervised and unsupervised learning, model validation, regression, time series and hypothesis testing.
Experience with ML frameworks such as Scikit-learn and, where relevant, XGBoost, PyTorch or TensorFlow.
Experience with automated pipelines and CI/CD, using version control and testing practices, preferably in Azure DevOps or GitHub.
Hands-on experience with Snowflake AI/ML tools (Snowpark ML, Cortex AI, Cortex Analyst, Cortex Search, AI Functions) and Snowflake connectors.
Experience analysing, modelling and integrating SAP and Salesforce data. This means understanding source data structures, business entities, relationships and transformation requirements.
Understanding of how AI/ML solutions run in production: monitoring, reliability, performance, cost management, root-cause analysis and continuous improvement.
Working knowledge of enterprise architecture, cloud security, privacy, compliance, data governance and Responsible AI principles.
Ability to turn business needs into technical solutions, explain options and trade-offs, and communicate clearly with technical and business stakeholders.
Fluent spoken and written English (minimum C1).

Desired Qualifications

Experience with LLM frameworks such as the Azure OpenAI SDK, LangChain, Semantic Kernel or equivalent.
Experience with other AI platforms and models (e.g., Anthropic, SLMs).
Microsoft certifications: Azure AI Engineer Associate (AI-102), Azure AI Apps and Agents Developer Associate (AI-103), Azure Data Scientist Associate (DP-100) or Machine Learning Operations Engineer Associate (AI-300).
Snowflake certifications, such as SnowPro Core or relevant GenAI certifications.
Experience using Azure DevOps for work planning, execution and reporting.
Experience with Copilot Studio, Power Platform, Microsoft Fabric, Power BI, Streamlit or other data visualisation tools.
Knowledge of Azure infrastructure for AI/ML workloads: networking, VNets/private endpoints, Entra ID, RBAC, managed identities, Key Vault, storage, containers, Azure Monitor and Application Insights.
Infrastructure as Code experience (Bicep or Terraform).
Experience mentoring colleagues or contributing to shared engineering standards and reusable assets.

Benefits

The chance to be part of a global company working on high-impact industrial projects.
A collaborative environment with continuous learning, advanced technologies and a strong development culture.
Room to grow on a solid technical career path at ABB.

Skills

PythonSQLAzure Machine LearningSnowflakeGenAIMLOpsSAPSalesforceLLMRAGembeddingsvector searchprompt engineeringAI agentsScikit-learnXGBoostPyTorchTensorFlowCI/CDAzure DevOpsGitHubSnowpark MLCortex AICortex SearchAI FunctionsAzure OpenAICopilot StudioPower PlatformCopilotAnthropic modelsMicrosoft FoundryStreamlitMicrosoft FabricPower BIAzure AI Engineer AssociateAzure AI Apps and Agents Developer AssociateAzure Data Scientist AssociateMachine Learning Operations Engineer AssociateSnowPro CoreBicepTerraform

#AI#Machine Learning#Data Science#GenAI#LLM#MLOps

About ABB

We are a technology leader in electrification and automation, enabling a more sustainable and resource-efficient future.

ABB is a technology leader in electrification and automation, enabling a more sustainable and resource-efficient future. The company’s solutions connect engineering know-how and software to optimize how things are manufactured, moved, powered and operated. Building on more than 130 years of excellence, ABB’s ~105,000 employees are committed to driving innovations that accelerate industrial transformation. www.abb.com\nPrivacy notice & house rules: https://social.abb/social-media-information\n\nBefore applying for a job at ABB , please read our Fraud Warning:…

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Company

ABB

Job Posted

1 day ago

Employment Type

Full Time

Work mode

Hybrid

Experience Level

Senior

Locations

Atlanta, United States

Boca Raton, United States

Raleigh, United States

San Francisco, United States

Qualification

Master

Applicants

Be an early applicant

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