AI/ML Engineer
Thermo Fisher Scientific10 days ago
Remote, Mexico or Tijuana, MexicoMid Level / Senior
Responsibilities
- Prototype, test, and implement data and AI use cases using Databricks, SAP Business AI, AWS, Azure, or other cloud AI services.
- Build and integrate LLM APIs, custom API connectors, and retrieval workflows for analytics deliverables.
- Acquire, cleanse, transform, and map data to create models for analytical reporting and AI applications.
- Design basic ETL/ELT pipelines, evaluate data sources, and develop data preparation and business rules.
- Automate repetitive data workflows, testing tasks, and monitoring scripts with Python and SQL.
- Create and maintain technical documentation for integrations and applications.
- Support incidents, requests, and operational activities according to standard ITSM lifecycles.
- Participate in on-call schedules for critical incidents and data pipeline issues.
Requirements
- 3–5 years of practical experience in data engineering, software development, or data analytics with hands-on exposure to modern data platforms.
- Strong Python proficiency, including Pandas and API integration, and proficiency with complex SQL queries.
- Practical experience with Databricks, PySpark, or similar cloud data platforms.
- Experience with LLM APIs such as OpenAI, Anthropic, or Azure OpenAI, or with API-driven integrations and prototypes.
- Hands-on familiarity with consuming REST APIs and modern AI frameworks.
- A degree in computer science, data science, software engineering, or an equivalent field is preferred.
- A master's degree in computer science or a related technical field is desirable.
- Familiarity with SAP data structures or SAP BW/4HANA, SAP Datasphere, CDS views, or SAP Business AI is desirable.
- Exposure to Model Context Protocol, LangChain, or LlamaIndex is desirable.
- Familiarity with SAP BOBJ, Power BI, or SAP Analytics Cloud is desirable.
- Ability to work independently and collaboratively across global cross-functional teams, with customer focus and willingness to learn enterprise systems.
Benefits
- Standard Monday–Friday work schedule in an office environment.
- Participation in on-call coverage for critical operational incidents and data pipeline issues.
Categories
AI ApplicationsData Engineering
About Thermo Fisher Scientific
Thermo Fisher Scientific builds analytical instruments, lab equipment and consumables, specialty diagnostics, and provides pharma services (CDMO and clinical research) for biotech, pharma, academic, and healthcare customers. It earns revenue through product sales, e-commerce distribution (Fisher Scientific), and contract services under brands such as Thermo Scientific, Applied Biosystems, Invitrogen, Patheon, and PPD. Headquartered in Waltham, MA, it is publicly traded on the NYSE (TMO) and was created by the 2006 merger of Thermo Electron and Fisher Scientific.