We are seeking a highly motivated data engineer with demonstrated experience scaling and delivering production quality data systems to join our Science team within Digital Farming Solutions at Bayer Crop Science. You will work closely with key partners, including data engineers and data scientists, to develop reliable, scalable and maintainable machine learning solutions. 

YOUR TASKS AND RESPONSIBILITIES  

The primary responsibilities of this role are to: 

• Write robust, well-documented code 

• Engage with colleagues with diverse technical backgrounds and expertise to understand feature, model and business requirements, and develop solutions to meet automation and scaling needs 

• Evaluate existing data and model pipelines, and provide recommendations to support business and technical requirements 

• Utilize tools and/or infrastructure developed by technical delivery partners to ensure proper data architectures and computational infrastructure is available to support rapid development and testing on machine and deep learning models that create value for our farmers 

• Collaborate across the Science organization to create high-quality, reproducible tools (e.g. templates, packages and dashboards) that will accelerate delivery of customer value 

• Undertake written & verbal communication with stakeholders in various parts of the organization in the form of detailed documentation and presentations 

• Chunk, clean, and format text into LLM-ready formats such as JSONL 

• Contribute to community guidelines for prompt/data hygiene, provenance, and safe data handling for LLMs 

WHO YOU ARE 

Bayer seeks an incumbent who possesses the following: 

Required: 

• Bachelor’s degree in data science, computer science, or related quantitative field 

• A minimum of 3 years' experience is required for the following 

• • Strong Python coding skills for development and visualizations, including experience with standard packages (numpy, pandas, matplotlib, seaborn) 

• • Familiar with Extract, Transform, and Load (ETL) processes and simple pipeline creation 

• Proficient use of SQL or Spark to extract and manipulate data from databases, data warehouses, and data lakes 

• Experience utilizing Git for collaborative code development 

• Experience with cloud-based platforms (AWS, GCP, Azure) and basic services (ie. S3, Lambda, Dataproc) 

• Experience with oral presentation and technical writing 

• Practical experience with newline-delimited data formats 

• Familiarity with text encoding (UTF-8) and common cleaning issues 

• Familiarity with tokenization concepts and context-window tradeoffs 

• Experience with prompt templates and basic prompt telemetry for debugging 

Preferred: 

• Excitement to learn new topics, develop new skills and use new tools 

• Experience with web services, api and database design 

• Experience applying data quality concepts 

• Familiarity with NOSQL tools like Hadoop (hive, pig, presto) and PySpark 

• Experience with virtual machines and cloud computing 

• Interdisciplinary communication and collaboration skills 

• Experience with application of statistics to environmental or agricultural problems 

• Expertise in data interoperability and analytics 

• Familiarity with NLP libraries and tokenizers 

• Familiarity with embeddings, vector DBs, and data-labeling workflows 

Employees can expect to be paid a salary of approximately $90k-130k. Additional compensation may include a bonus or incentive program (if relevant).  Additional benefits include health care, vision, dental, retirement, PTO, sick leave, etc..  This salary (or salary range) is merely an estimate and may vary based on an applicant’s location, market data/ranges, an applicant’s skills and prior relevant experience, certain degrees and certifications, and other relevant factors. 

This posting will be available for application until at least 2/13/26.