ML Engineer
IND - Chennai Office
Technology impacts everything we do. Pfizer’s digital and ‘data first’ strategy focuses on implementing impactful and innovative technology solutions across all functions from research to manufacturing. Whether you are digitizing drug discovery and development, identifying solutions, or making our work easier and faster, you will be making a difference to countless lives.
ROLE SUMMARY
The Digital Manufacturing Team is responsible for the delivery of Pfizer’s Core Digital Manufacturing Operations Management (MoM) capabilities at every level of the PGS Plant Network (ISA 95 Levels 0-4). These solutions are critical to Manufacturing Execution, Manufacturing Process Intelligence and Production Optimization that aim to improve product quality, increase asset utilization/uptime, automate manual workflows, and streamline plant floor operations. The Digital Manufacturing Team provides common application platforms and solution capabilities for Digital Plant, Manufacturing Operations, Manufacturing Execution, Manufacturing Insights and Digital Quality solutions, while ensuring a unified User Centric Design. Key to the success of this transformative digital mindset is the secure, seamless flow of contextualized data from the device & control levels, all the way to the top of the Enterprise. These solutions are deployed across more than fifty manufacturing & center locations across the PGS Globally. Major Core Solutions and team capabilities for the Manufacturing Operations Solutions Team include:
- This group supports the design, development, delivery and digitization of PGS Manufacturing and Engineering processes. Process Areas (Systems) include Industrial Internet of Things, Enterprise Data Historians, Cybersecurity, Manufacturing Operations Solutions (Manufacturing Intelligence, EAMS Maintenance Mgmt & Calibration, Capital Mgmt, Permit to Work, OEE/RTE, Engineering systems), Manufacturing Execution Systems and Manufacturing Innovative Technologies including AI/ML and Generative model based digital solutions.
The ML Engineer plays a key role in delivering the future of Advanced Manufacturing Capabilities within the Digital Manufacturing Organization. This colleague will collaborate closely with Data Scientists and other engineering teams to design, implement, and maintain systems that operationalize and scale our data and machine learning pipelines. Their expertise in machine learning operations and cloud infrastructure will be crucial in ensuring the successful development, deployment, and management of our production machine learning systems. The ideal candidate will have a passion for cutting-edge technology, complex problem-solving, and delivering high-quality solutions.
ROLE RESPONSIBILITIES
- Collaborate with Data Scientists and product teams to understand user stories and convert them into technical requirements for machine learning solutions.
- Design, build, and deploy production machine learning systems on AWS cloud infrastructure within the digital teams.
- Implement and optimize monitoring, logging, and alerting systems to ensure the health and performance of deployed machine learning models.
- Work closely with DevOps and infrastructure teams to ensure seamless integration and deployment of machine learning pipelines.
- Automate and streamline the end-to-end machine learning workflow, including data ingestion, feature engineering, model training, evaluation, and deployment.
- Implement best practices for version control, model reproducibility, and model deployment.
- Collaborate with cross-functional teams to identify and address performance bottlenecks, scalability challenges, and data quality issues.
- Continuously evaluate and adopt emerging technologies and tools to improve the efficiency and effectiveness of machine learning operations.
BASIC QUALIFICATIONS
- Bachelor’s degree in computer science, Information Systems, or a related field.
- 6+ years of work experience in medium to ML, including designing, building, and deploying production machine learning systems.
- Strong expertise in deploying machine learning models on AWS cloud infrastructure.
PREFERRED QUALIFICATIONS
- Advanced SQL skills and experience with relational databases and database design.
- Proficiency in Python and SQL for data manipulation, analysis, and model development.
- Strong knowledge of Linux, Docker, and Kubernetes for containerization and orchestration of machine learning applications.
- Passion for learning and staying updated with the latest advancements in machine learning, MLOps, and cloud technologies.
- Excellent communication skills, with the ability to effectively communicate complex technical concepts to both technical and non-technical stakeholders.
Work Location Assignment: Flexible
Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.
Information & Business Tech* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS Computer Science Data quality DevOps Docker Drug discovery Engineering Feature engineering Industrial Kubernetes Linux Machine Learning ML models MLOps Model deployment Model training Pipelines Python RDBMS Research SQL
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