As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers.
Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up. Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful.
At Target, we have a timeless purpose and a proven strategy. And that hasn’t happened by accident. Some of the best minds from different backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Target’s global team and has more than 4,000 team members supporting the company’s global strategy and operations.
As a Lead AI Engineer in Data Sciences, you will play crucial role in designing, implementing, and optimizing the AI solutions in production. Additionally, you’ll apply best practices in software design, participate in code reviews, create a maintainable well-tested codebase with relevant documentation. We will look to you to understand and actively follow foundational programming principles (best practices, know about unit tests, code organization, basics of CI/CD etc.) and create a well-maintainable & tested codebase with relevant documentation. You will get the opportunity to develop in one or more approved programming languages (Java, Scala, Python, R) and learn and adhere to best practices in data analysis and data understanding.
The Content Creation team within Data Sciences will help build AI solutionsleveraging GenAI, computer vision and traditional ML models for various marketing or site content use-cases. The team will play a crucial role in helping Targetdrive relevancy with guests.
Lead Development of Generative AI Applications: Architect and develop advanced generative AI solutions that support business objectives, ensuring high performance and scalability.
Performance Tuning & Optimization: Identify bottlenecks in applications and implement strategies to improve performance. Optimize machine learning models for efficiency in production environments.
Collaborate Cross-Functionally: Work closely with data scientists, product managers, and other stakeholders to gather requirements and transform them into robust technical solutions.
Mentor Junior Engineers: Provide guidance and mentorship to team members on best practices in coding standards, architectural design, and machine learning techniques.
Research & Innovation: Stay abreast of the latest advancements in the field of Artificial Intelligence. Propose new ideas that could lead to innovations within the organization.
Deployment & Scaling Strategies: Lead the deployment process of applications on cloud platforms while ensuring they are scalable to handle increasing loads without compromising performance.