Engineer II

Edwards Lifesciences is establishing a new IT Innovation Hub in Pune, India, to expand its global technology capabilities. This role, Engineer II, AI/Machine Learning, is crucial for identifying business challenges and opportunities that can be addressed with AI/ML solutions. You will be responsible for designing, developing, and testing rapid AI/ML prototypes to resolve these identified business gaps.

How you will make an impact:

• Develop and deploy scalable and efficient AI/ML models for both prototyping and production environments.
• Collaborate with cross-functional teams, including data scientists, software engineers, product managers, and business leads, to define requirements and conceptualize AI/ML-driven solutions.
• Engage in agile development processes, participating in sprint planning, daily stand-ups, and presenting prototypes or milestone updates.
• Adhere to established tools, standards, and architectural best practices to maintain software quality and scalability.
• Provide ongoing maintenance, operation, and technical support for deployed production solutions.
• Conduct research and experimentation to explore novel AI/ML techniques, tools, and frameworks.
• Ensure all code and model development is thoroughly documented and follows rigorous engineering best practices.
• Perform other incidental duties as required.

What You'll Need (Required):

• Bachelor's Degree in Engineering or a related technical field.
• A minimum of 2 years of experience in Software Development or Engineering, with a proven track record of solid performance in roles involving collaboration with cross-functional teams on enterprise-level or complex system implementations.
• Experience with cloud platforms such as AWS or other cloud infrastructure services for model deployment and data storage.
• Proficiency in programming languages such as Python, Java, C++, or similar.

What Else We Look For (Preferred):

• Experience with machine learning libraries and frameworks like TensorFlow, PyTorch, Scikit-learn, Keras, etc.
• A strong understanding of machine learning algorithms, statistical principles, and data structures.
• Familiarity with big data technologies such as Hadoop, Spark, or similar tools.
• Solid experience with version control systems, particularly Git, and agile development methodologies.
• Experience with deep learning techniques, including CNNs, RNNs, GANs, etc.
• Knowledge of data engineering practices and tools, such as Apache Kafka and Airflow.
• Excellent communication skills and the ability to collaborate effectively within cross-functional teams.
• Strong problem-solving and debugging abilities.
• Meticulous attention to detail.
• Capability to manage competing priorities in a fast-paced environment.
• Adherence to all company rules and requirements, including safety protocols and environmental regulations, and taking necessary control measures to prevent harm and pollution.