What You'll Do
Architect and implement advanced deep learning models for multimodal
recommendation systems, processing diverse data types including text, images, user
behavior, item features, offer data, and contextual signals.
Lead the development and optimization of generative AI applications for personalized
product discovery, search enhancement, and customer engagement.
Expert in leveraging cutting-edge GenAI techniques, prompt engineering, transformer
architectures, and own end-to-end development of scalable AI/ML pipelines
Design and maintain highly scalable ML infrastructure using GCP services (Vertex AI,
BigTable, BigQuery, Cloud Composer) capable of handling millions of daily predictions.
Build and optimize end-to-end ML pipelines for model training, deployment, and
monitoring at scale.
Drive technical strategy and architecture decisions for the personalization platform.
Collaborate with product managers, data scientists, and engineers to translate business
requirements into robust technical solutions.
Lead experimentation strategies with measurable KPIs including adoption, conversion &
retention.
Mentor junior team members and contribute to building a strong technical culture.
We are a company committed to creating inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity employer that believes everyone matters. Qualified candidates will receive consideration for employment opportunities without regard to race, religion, sex, age, marital status, national origin, sexual orientation, citizenship status, disability, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to
Human Resources Request Form. The EEOC "Know Your Rights" Poster is available
here.
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https://insightglobal.com/workforce-privacy-policy/ .
Master's or PhD in Computer Science, Machine Learning, or related field.
5+ years of experience in machine learning engineering, with a focus on recommendation
systems or personalization.
Strong expertise in deep learning frameworks (PyTorch or TensorFlow) and building
production-grade ML systems.
Proven experience with GCP services and ML infrastructure at scale.
Proficient in Python, SQL, and cloud-native development.
Experience with containerization (Docker) and orchestration (Kubernetes).
Track record of deploying ML models to production at scale.
Benefit packages for this role will start on the 31st day of employment and include medical, dental, and vision insurance, as well as HSA, FSA, and DCFSA account options, and 401k retirement account access with employer matching. Employees in this role are also entitled to paid sick leave and/or other paid time off as provided by applicable law.