Data Scientist - AI/ML Engineering & Machine Learning Modeling

Bayer AG; United States; Remote; USD 90,000 - 120,000; Part time

Job summary

A leading agricultural science company is seeking a Data Scientist for AI/ML Engineering and Machine Learning Modeling. The role will focus on designing, building, and deploying AI solutions, transforming business challenges into production-ready services. Candidates must have a Master's degree with relevant experience and strong analytical skills. Join a global AI/ML team providing impactful solutions across diverse challenges. The position offers remote flexibility and collaborates within small teams fostering innovation.

Qualifications

• Master's degree with 1+ years of experience, or PhD in a quantitative field.
• Hands-on experience with deep learning frameworks.
• Expertise in AI/ML algorithms and embedding techniques.

Responsibilities

• Collaborate with teams to define AI/ML solutions.
• Design and deploy machine learning models.
• Create applications delivering insights to users.
• Implement CI/CD and testing for data projects.

Skills

Python

SQL

scikit-learn

XGBoost

LightGBM

PyTorch

TensorFlow

Langchain

Google ADK

Streamlit

Plotly Dash

BigQuery

Vertex AI

Cloud Run

Gemini Enterprise

AWS S3

AWS Lambda

AWS ECS

AWS SageMaker

Education

Master's degree in Data Science or a related quantitative field

Job description

Data Scientist ? AI/ML Engineering & Machine Learning Modeling (Contract)

Remote

Contract (5 months 28 days)

Published 4 days ago

SQL

LLM - Large Language Model

Python

Job Summary:

We are seeking a highly skilled and hands‑on data scientist who combines deep analytical expertise with strong engineering capabilities to design, build, and deploy AI and machine learning solutions at scale. In this role, you will serve as a bridge between business stakeholders and technical teams, transforming complex business challenges into measurable, production‑ready AI/ML services. You will work across modern cloud platforms to develop everything from generative AI agents to traditional machine learning models, while also creating intuitive applications that deliver insights directly to end users. This position offers the opportunity to work on diverse problems spanning classification, forecasting, recommendation systems, and cutting‑edge generative AI applications, all while contributing to a culture of technical excellence and best practices.

Responsibilities

• Collaborate with business and engineering teams to translate business problems into well‑defined AI/ML solutions with clear success metrics
• Design, train, validate, and deploy machine learning models for classification, regression, recommendation, and time‑series forecasting applications
• Select appropriate algorithms, features, and evaluation strategies aligned with business objectives
• Develop and evaluate generative AI agent applications using frameworks such as Langchain and Google ADK
• Leverage advanced techniques including retrieval‑augmented generation, prompt engineering, and vector database integration
• Build and maintain reliable data pipelines and model inference endpoints across cloud platforms
• Implement CI/CD workflows, automated testing, and monitoring systems for machine learning and data projects
• Create lightweight dashboards and internal applications to deliver models and insights to stakeholders
• Write comprehensive model documentation covering problem formulation, modeling approach, validation methodology, data requirements, and deployment procedures
• Promote coding best practices, reproducibility, and knowledge sharing across the global data science organization

Skills

• Advanced proficiency in Python and SQL
• Experience with scikit‑learn, XGBoost, and LightGBM
• Proficiency in at least one deep learning framework (PyTorch or TensorFlow)
• Hands‑on experience building generative AI and large language model applications
• Expertise in developing agentic workflows
• Strong ability to build reliable data pipelines with focus on data quality and lineage
• Experience implementing CI/CD for machine learning and data projects using tools like GitHub Actions, Cloud Build, or AWS CodeBuild/CodePipeline
• Practical experience developing internal dashboards and applications using Streamlit and/or Plotly Dash
• Working knowledge of Google Cloud Platform services including BigQuery, Vertex AI, Cloud Run, and Gemini Enterprise
• Working knowledge of AWS services including S3, Lambda, ECS, and SageMaker
• Deep understanding of AI/ML algorithms including their intuition, assumptions, statistical theory, computational complexity, and appropriate use cases

Qualifications

• Master's degree with 1+ years of experience, or PhD in Data Science, Computer Science, Applied Mathematics, Statistics, Econometrics, or related quantitative field

This is an exceptional opportunity to join a rapidly growing global AI/ML team of over 26 cross‑functional members within a larger data science organization of 70+ professionals. You will work in small, autonomous project teams that foster close collaboration and meaningful impact, while contributing to innovative solutions that support business operations across a major agricultural science company. The role offers significant autonomy, exposure to diverse technical challenges, and the chance to shape best practices in a dynamic, forward‑thinking environment.