Staff Machine Learning Eng

At Bayer we're visionaries, driven to solve the world's toughest challenges and striving for a world where 'Health for all Hunger for none' is no longer a dream, but a real possibility. We're doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining 'impossible'. There are so many reasons to join us. If you're hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there's only one choice.

Staff Machine Learning Eng

Position Overview:

As a Major Tasks Infrastructure Development professional, you play a crucial role in designing and implementing scalable AI/ML infrastructure to support model training, evaluation, and deployment. Collaborating with DevOps and IT teams, you ensure the infrastructure meets performance and security requirements. You lead the deployment of machine learning models into production environments, ensuring seamless integration with the discovery environment and existing systems. Your role includes implementing security best practices for machine learning models and data, optimizing models for scalability and performance, and automating data preprocessing and model training processes. You work closely with cross-functional teams, including data scientists, software engineers, and business stakeholders, to align machine learning initiatives with organizational goals.

YOUR TASKS AND RESPONSIBILITIES:

• Design and implement scalable AI/ML infrastructure to support model training, evaluation, and deployment;
• Collaborate with DevOps and IT teams to ensure infrastructure meets performance and security requirements;
• Lead the deployment of machine learning models into production environments, developing CI/CD pipelines for seamless integration;
• Implement security best practices for machine learning models and data, conducting regular security assessments;
• Optimize machine learning models for scalability and performance;
• Automate data preprocessing, model training, and evaluation processes;
• Monitor deployed models for performance and implement strategies for model retraining and updates;
• Provide technical guidance and mentorship to junior team members.

WHO YOU ARE:

Bayer seeks an incumbent who possesses the following:

Required Qualifications:

• Bachelor's or Master's degree in Computer Science, Data Science, or related field;
• Proficiency in programming languages such as Python, Java, or Scala, with experience in machine learning libraries;
• Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment;
• Strong communication skills.

Preferred Qualifications:

• 4+ years of experience in machine learning libraries (e.g., TensorFlow, PyTorch);
• 3+ years of experience in cloud platforms (e.g., AWS, Azure, Google Cloud), containerization (e.g., Docker, Kubernetes), and orchestration technologies (e.g., Airflow);
• 3+ years of experience in machine learning and data handling security best practices;
• 3+ years of experience in data engineering practices and big data technologies (e.g., Hadoop, Spark);
• Previous experience in a leadership or mentoring role is a plus.

YOUR APPLICATION
Bayer offers a wide variety of competitive compensation and benefits programs. If you meet the requirements of this unique opportunity, and want to impact our mission Science for a better life, we encourage you to apply now. Be part of something bigger. Be you. Be Bayer.
To all recruitment agencies: Bayer does not accept unsolicited third party resumes.

Bayer is an Equal Opportunity Employer/Disabled/Veterans

Bayer is committed to providing access and reasonable accommodations in its application process for individuals with disabilities and encourages applicants with disabilities to request any needed accommodation(s) using the contact information below.
Bayer is an E-Verify Employer. Location: United States : Missouri : Chesterfield Division: Crop Science Reference Code: 848012 Contact Us Email: