IBU China Machine Learning Operations Engineers at Lilly Bangalore

4 weeks ago


Bengaluru, India Lilly Full time

We’re looking for people who are determined to make life better for people around the world.

Contact Name: Shubhra Verma

Contact Details:

JD for MLOps team member for China team

Job Description

At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our 39,000 employees work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the globe.

Business Units Information and Digital Solutions (IDS) is a global organization strategically positioned so that through information and technology leadership and solutions, we create meaningful connections and remarkable experiences, so people feel genuinely cared for. The Business Unit IDS organization is accountable for designing, developing, and supporting commercial or customer engagement services and capabilities that span multiple Business Units (Bio-Medicines, Diabetes, Oncology, International), functions, geographies, and digital channels. The areas supported by Business Unit IDS includes: Customer Operations, Marketing and Commercial Operations, Medical Affairs, Market Research, Pricing, Reimbursement and Access, Customer Support Programs, Digital Production and Distribution, Global Patient Outcomes, and Real-World Evidence.

We are seeking a talented and experienced MLOps Engineer/ Specialist to join our team. The ideal candidate will play a crucial role in managing the deployment, monitoring, and optimization of machine learning models in our production environment. The MLOps Engineer/ Specialist will collaborate closely with data engineers, software engineers, and other stakeholders to ensure the seamless integration of machine learning solutions into our systems.

Responsibilities :

• Develop and maintain automated pipelines for model training, validation, deployment, and monitoring.

• Implement infrastructure and tools for scalable and reliable model deployment in production environments.

• Collaborate with data scientists and software engineers to package machine learning models for deployment using containerization technologies (e.g., Docker, Kubernetes).

• Optimize model inference speed and resource utilization for real-time and batch processing applications as needed.

• Ensure compliance with data privacy and security regulations in all aspects of model deployment and operation.

• Stay up-to-date with MLOps best practices and propose improvements when applicable.

• Provide technical guidance and support to cross-functional teams on MLOps-related initiatives.

• Bachelor's in computer science, Engineering, or related field.

• 5 years of experience in software engineering, data engineering, or related roles.

• Proficiency with AWS machine learning services (Sagemaker, OpenSearch, Glue, EMR, …)

• Hands-on experience with cloud platforms such as AWS, Azure.

• Understanding of machine learning concepts and frameworks (e.g., TensorFlow, PyTorch).

• Proficiency in Python programming including data processing, ML model building.

• Familiarity with DevOps practices and tools (e.g., Docker, CI/CD, Git, Jenkins).

• Excellent problem-solving skills and attention to detail.

• Effective communication and collaboration skills in a cross-functional team environment.

• Experience with NVIDIA GPUs and leveraging GPU acceleration for deep learning workloads is advantageous.

• Plus if have Prompt engineering experience but not must.

Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.

#WeAreLilly



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