Senior AI Engineer

Bayer (Schweiz) AG; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

Bayer (Schweiz) AG is seeking an AI/ML Engineer to lead the design and deployment of advanced ML models in cross-functional teams. The role emphasizes productionizing AI solutions using AWS/Azure/GCP and ensuring data quality and reliability in production.

The ideal candidate has strong Python or R skills, experience with TensorFlow/PyTorch/Scikit-learn, NLP or CV expertise, and exposure to big data and Azure DevOps in an Agile environment.

Qualifications

• Master's or PhD in CS/IT/DS/AI or Bachelor's with 8+ years experience.
• Proven AI/ML engineer experience.
• Experience deploying ML models and AI systems.
• Proficient in Python or R.
• Strong knowledge of TensorFlow, PyTorch, Scikit-learn.
• Experience with NLP or computer vision.
• Familiarity with Hadoop/Spark and cloud platforms (AWS/Azure/Google Cloud).
• Strong analytical skills and communication.
• Ability to collaborate in cross-functional teams.
• Experience with Agile methodologies and Azure DevOps.

Responsibilities

• Lead design and development of ML models in cross-functional teams.
• Lead scalable AI product implementations aligned with business objectives.
• Leverage cloud technologies to productionize ML models for deployment.
• Provide operational support for ML models ensuring reliability.
• Establish data quality checks and detect data drift.

Skills

AI/ML Engineer

Python

R

TensorFlow

PyTorch

Scikit-learn

NLP

Computer Vision

Big data

Hadoop

Spark

Cloud Platforms

AWS

Azure

GCP

Data quality

Data drift

Agile

CI/CD

DevOps

Azure DevOps

Docker

Kubernetes

SQL

CosmosDB

MongoDB

PostgreSQL

Databricks

Kafka

Education

Master's/PhD in CS/IT/DS/AI or Bachelor's +8 years

Tools

Azure DevOps

Docker

Kubernetes

Databricks

Spark

CosmosDB

MongoDB

SQL

PostgreSQL

Job description

Responsibilities

Lead the design and development of innovative machine learning models and algorithms in cross‑functional teams to effectively address specific business challenges. Lead the implementation of scalable AI products, ensuring alignment with user requirements and strategic business objectives. Leverage state‑of‑the‑art cloud technologies (e.g. AWS, Azure, Google Cloud) to optimize the industrialization of machine learning models and AI solutions for production deployment. Provide expert operational support and guidance for machine learning models and algorithms, ensuring their reliability and performance in production environments. Establish and promote advanced data quality assurance processes, including validation checks and proactive data drift detection mechanisms, to ensure data consistency and integrity.

Requirements

• Required Master's or Ph.D. degree in Computer Science, Information Technology, Data Science, Artificial Intelligence or a related field or Bachelor's with minimum 8 years experience.
• Proven experience as an AI Engineer, Machine Learning Engineer, or similar role.
• Experience in developing and deploying machine learning models and AI systems.
• Proficiency in programming languages such as Python or R.
• Strong knowledge of machine learning frameworks (TensorFlow, PyTorch, Scikit‑learn).
• Experience with natural language processing (NLP), computer vision, or other AI techniques.
• Familiarity with big data technologies (Hadoop, Spark) and cloud platforms (AWS, Azure, Google Cloud).
• Strong analytical skills and the ability to work with complex datasets.
• Excellent problem‑solving skills with a focus on developing innovative AI solutions.
• Excellent verbal and written communication skills.
• Ability to work collaboratively in a cross‑functional team environment.
• Strong organizational skills and the ability to manage multiple AI projects simultaneously.
• Experience with Agile methodologies and tools (Azure DevOps, Scrum).
• Azure Expertise: Deep understanding of the Azure ecosystem, specifically Azure AI, Azure Machine Learning, Compute, Storage, Networks and Azure Arc, Containers (registry, runtimes), Events, Functions, Azure Identity tooling.
• Edge/Hybrid Cloud: Practical experience with hybrid cloud or edge computing infrastructure (e.g., Azure Stack HCI, Kubernetes on‑premises).
• Programming: Strong proficiency in Python 3 and familiarity with modern AI and automation development stacks and Powershell.
• System Architecture: Solid understanding of distributed systems, containerization (Docker/Kubernetes), and API design.
• Teams Bot design and implementation: Microsoft Teams Bot integrations; understanding of maintaining and publishing bots, React.
• Databases: Azure Databases (CosmosDB, MongoDB, SQL Database, PostgreSQL).
• Data Engineering: Databricks (Spark/OSP), Log Analytics, Kafka.
• Relevant certifications in AI, machine learning, or data science (e.g., AWS Certified Cloud / AI practitioner, Azure Fundamentals; Azure Solutions Architect or Azure AI Engineer certification).