AI/ML Engineer

Work Schedule

Environmental Conditions

Job Description

When you’re part of Thermo Fisher Scientific, you’ll do challenging work, and be part of a team that values performance, quality and innovation. As part of a successful, growing global organization, you will be encouraged to perform at your best. With revenues of more than $40 billion and the largest investment in R&D in the industry, we give our people the resources and opportunities to make significant contributions to the world. 

Location/Division Specific Information 

Business Intelligence Delivery and Operations team is part of corporate IT function under Enterprise Technology Organization. BI Team is responsible for data service, data lake and analytics services for internal customers of Thermo Fisher Scientific 

How will you make an impact? 

The Data engineer Developer role provides an opportunity for data job seekers who currently hold a data science, data analytics, computer engineering, or like engineering degree. Individuals will be working with team of data analyst, data engineers in a fast-paced bi analytics environment. The candidate will contribute to development projects, pilots and advance best design practices. 

What will you do? 

• AI & Data Solutioning: Support the prototyping, testing, and implementation of data and AI use cases using Databricks, SAP Business AI, or any cloud AI services 
  ( aws or azure) 

• LLM & API Integration: Assist in building and integrating AI capabilities using LLM APIs, custom API connectors (such as MCP), or retrieval workflows to enhance analytics deliverables. 

• Data Engineering & Modeling: Participate in data acquisition, cleansing, transformation, and mapping to build clean data models for Analytical reporting and AI applications or use cases within SAP and non-SAP ecosystem. 

• Pipeline Development & ETL: Perform data source evaluations, design basic ETL/ELT pipelines, and perform data preparation and business rule development. 

• Process Automation: Identify and automate repetitive data workflows, testing tasks, and monitoring scripts using Python and SQL. 

• Documentation & Support: Create and maintain technical documentation for integrations and applications. Support incidents, requests, and operational support activities per standard ITSM lifecycles. 

• Operational Readiness: Participate in on-call schedules to address critical operational incidents and data pipeline issues as needed. 

• Performs all other related duties as assigned. 

How will you get here? 

• Have 3–5 years of practical experience in data engineering, software development, or data analytics with hands-on exposure to modern data platforms. 

• Hands-on familiarity with writing clean Python code, consuming REST APIs, and working with modern AI frameworks. 

• Ability to work independently and as a member of a cross-functional team across the globe. 

• Strong willingness to learn enterprise systems (like SAP) and innovate new solutions. 

• Passionate about applications, analytics, and end-user productivity. 

• Exceptional customer focus. 

• Degree with major in computer science, data science, software engineering (or equivalent) from an accredited university (preferred). 

• Master's degree in computer science or related technical field from an accredited university (desired). 

Tool & Technology Skills 

• Programming & SQL: Strong proficiency in Python (Pandas, API integration) and complex SQL queries (Must have). 

• Modern Data Stack: Practical experience with Databricks, PySpark, or similar cloud data platforms (Must have). 

• AI & API Integration: Experience working with LLM APIs (e.g., OpenAI, Anthropic, Azure OpenAI) or building API-driven integrations/prototypes (Must have). 

• SAP Knowledge: Basic familiarity with SAP data structures or exposure to tools like SAP BW/4HANA, SAP Datasphere, CDS views, or SAP Business AI (Desirable). 

• Protocols & Frameworks: Exposure to Model Context Protocol (MCP) concepts or orchestration frameworks like LangChain/LlamaIndex (Desirable). 

• BI & ETL Tools: Familiarity with traditional BI reporting tools (e.g., SAP BOBJ, Power BI) or SAP Analytics Cloud (Desirable).