Lead AI Engineer- Content Creation

About Us

As a Fortune 50 company with more than 400000 team members worldwide Target is an iconic brand and one of Americas 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 youll build relationships by being authentic and respectful.

Overview about TII

At Target we have a timeless purpose and a proven strategy. And that hasnt 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 Targets global team and has more than 4000 team members supporting the companys global strategy and operations.

Pyramid Overview

As a Lead AI Engineer in Data Sciences you will play crucial role in designing implementing and optimizing the AI solutions in production. Additionally youll 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.

Team Overview

The Content Creation team within Data Sciences will help build AI solutions leveraging GenAI computer vision and traditional ML models for various marketing or site content use-cases. The team will play a crucial role in helping Target drive relevancy with guests.

Position Overview

• 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.

• Documentation & Quality Assurance: Develop comprehensive documentation for projects undertaken. Implement rigorous testing methodologies to ensure high-quality deliverables.

About You

• 4-year degree in Quantitative disciplines (Science Technology Engineering Mathematics) or equivalent experience

• Masters in computer science or equivalent industry experience

• Over 6 plus years of experience in end-to-end application development data exploration data pipelining API design optimization of model latency in production environments at scale.

• Experience in working with image text data embeddings building & deploying vision models integrating with Gen AI services

• Strong expertise in Machine Learning frameworks such as TensorFlow PyTorch or similar libraries; experience with Generative Adversarial Networks or Diffusion Models is desirable

• Hands-on experience in libraries like NumPy SciPy Pandas OpenCV SpaCY NLTK is expected

• Experience in optimizing ML model performance using techniques such as hyperparameter tuning feature selection and distributed training

• Good understanding of Big Data and Distributed Architecture- specifically Hadoop Hive Spark Docker Kubernetes and Kafka

• Experience working on GPUs is preferred

• Proven track record of optimizing machine learning models for performance improvements across various platforms including cloud services (AWS Google Cloud Platform)

• Expertise in MLOps frameworks and hands on experience in MLOps tools like Kubeflow MLFlow or Sagemaker

• Deep understanding of system architecture principles related to scalability and robust application design.

• Excellent communication problem-solving skills combined with strong analytical abilities.

• Proven leadership skills with experience mentoring junior engineers effectively

Know More About Us here:

• Life at Target-