1 hour ago
Sarajevo, Bosnia and Herzegovina +3 moreSenior
Responsibilities
- Work with business stakeholders and data professionals to define needs, success measures, risks, data requirements, and solution ownership.
- Select and design scalable AI/ML, GenAI, analytics, automation, or conventional solutions aligned with enterprise architecture, security, and governance standards.
- Develop, validate, deploy, and operate production AI/ML and GenAI solutions using Python, SQL, Azure Machine Learning, Microsoft Foundry, and approved technologies.
- Build predictive models, RAG applications, embeddings and vector search solutions, prompt and context engineering, AI agents, APIs, orchestration, retrieval, and enterprise data integrations.
- Integrate LLM-based solutions and conversational agents with Microsoft Foundry, Azure OpenAI, Copilot Studio, Power Platform, and other AI platforms.
- Use Snowflake, SAP, and Salesforce data to deliver predictive models, GenAI applications, AI agents, and reliable data ingestion and processing.
- Develop reusable pipelines and components for data preparation, feature engineering, training, inference, evaluation, testing, deployment, and retraining.
- Evaluate model accuracy, explainability, grounding, agent behavior, safety, business value, performance, reliability, and cost.
- Establish and operate MLOps/AIOps practices including monitoring, drift detection, cost monitoring, incident analysis, retraining, and continuous improvement.
- Apply information security, privacy, compliance, identity and access management, secrets management, Responsible AI, and data governance requirements.
- Own deliverables end to end, document solution logic and operational requirements, communicate risks, and collaborate with analysts, data scientists, engineers, platform specialists, and domain experts.
- Contribute reusable assets, engineering standards, 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, including 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 LLMs, RAG, embeddings, vector search, prompt and context engineering, agent design, and evaluation.
- Working knowledge of supervised and unsupervised learning, model validation, regression, time series, and hypothesis testing.
- Experience with Scikit-learn and, where relevant, XGBoost, PyTorch, or TensorFlow.
- Experience with automated pipelines, CI/CD, version control, and testing practices, preferably using Azure DevOps or GitHub.
- Hands-on experience with Snowflake AI/ML tools, Snowflake connectors, and analysis and integration of SAP and Salesforce data.
- Understanding of production monitoring, reliability, performance, cost management, root-cause analysis, continuous improvement, enterprise architecture, cloud security, privacy, compliance, data governance, and Responsible AI.
- Fluent spoken and written English at minimum C1 level.
- Preferred qualifications include experience with Azure OpenAI SDK, LangChain, Semantic Kernel, Anthropic models, Copilot Studio, Power Platform, Microsoft Fabric, Power BI, Streamlit, Azure infrastructure, Bicep, Terraform, and mentoring.
- Preferred certifications include Azure AI Engineer Associate, Azure AI Apps and Agents Developer Associate, Azure Data Scientist Associate, Machine Learning Operations Engineer Associate, SnowPro Core, or relevant GenAI certifications.
Benefits
- Hybrid work model.
- Opportunity to work for a global company on high-impact industrial projects.
- Collaborative environment with continuous learning, advanced technologies, and a strong development culture.
- Technical career growth opportunities at ABB.
- Inclusive workplace welcoming people from diverse backgrounds and experiences.
Categories
About ABB
ABB builds electrification, robotics, motion, and process automation hardware and software for industrial, utility, transportation, and infrastructure customers. Its portfolio spans motors and drives, robots, PLCs, switchgear, and EV charging, sold as equipment, systems, and services under the ABB Ability platform. Formed in 1988 and headquartered in Zurich, it is a public company traded on the SIX Swiss Exchange and NYSE.