Wizard

Design and maintain infrastructure for deploying and monitoring machine learning models at scale. Automate end-to-end model pipelines and ensure ML systems are secure and scalable in production. | 5+ years of experience in MLOps and a Bachelor's or Master's in Computer Science or a related field are required. Strong expertise in Python and ML/DS libraries, as well as experience with cloud platforms, is essential. | About Us Wizard is the top-performing AI Shopping Agent, delivering the best products from across the web with unmatched accuracy, quality, and trust. The Role We are seeking a Senior MLOps Engineer to design and maintain the infrastructure that powers our production machine learning systems. You will work at the intersection of ML and infrastructure, building the pipelines, tooling and monitoring that enables fast, reliable model deployment at scale. Key Responsibilities: Design, build and maintain infrastructure for deploying, monitoring and updating machine learning models at scale Automate end to end model pipelines from ingestion and preprocessing to training, validation and deployment Implement monitoring for model performance, accuracy, drift and latency Ensure ML systems are secure, cost efficient and scalable in production Document and continuously improve ML infrastructure, workflows and tooling Partner with ML engineers, scientists and product to move models seamlessly from research to production Apply software engineering best practices (testing, CI/CD, version control) to ML systems You 5+ years of experience in ML Ops including ownership of production ML systems Bachelor’s or Master’s in Computer Science or a related field Strong expertise in Python and ML/DS libraries (e.g. TensorFlow, PyTorch) Experience with machine learning lifecycle management tools Hands on experience deploying and monitoring deep learning models Strong knowledge of cloud platforms such as AWS, Azure, or GCP The expected salary for this role is $185,000 - $210,000 depending on skills and experiences.

Design and evolve scalable data infrastructure and build real-time and batch data processing pipelines. Partner with various teams to provide data solutions for business-critical needs. | Candidates should have over 5 years of experience in software development and data engineering, with a strong focus on Spark and distributed systems. A Bachelor's degree in Computer Science or a related field is required, along with proficiency in Python and database management. | About Us Wizard is the top-performing AI Shopping Agent, delivering the best products from across the web with unmatched accuracy, quality, and trust. The Role We are seeking a Staff Data Engineer with deep expertise in Spark to join our data team. This is a hands-on technical role for someone passionate about building scalable data systems, mentoring engineers and shaping data strategy. You’ll architect systems that power high performance batch and real time data processing, enable advanced analytics and accelerate our AI initiatives. Key Responsibilities: Design and evolve scalable, distributed data infrastructure across cloud platforms Build and maintain real time and batch data processing pipelines supporting analytics and AI/ML workloads Develop and manage integrations with third party e-commerce platforms to expand our data ecosystem Ensure data availability, reliability and quality through monitoring and automated auditing Partner with engineering, AI and product teams on data solutions for business critical needs Mentor and support data engineers, establishing best practices and code quality standards You 5+ years of software development and data engineering experience with demonstrated ownership of production grade data infrastructure Bachelor's degree in Computer Science or a related field, or equivalent practical experience. Deep expertise scaling Spark in production (Databricks, EMR, etc) Strong understanding of distributed computing and modern data modeling for scalable systems Proficient in Python with experience implementing software engineering best practices Hands-on experience with both relational (MySQL / PostgreSQL) and NoSQL (MongoDB, DynamoDB, Cassandra) databases Strong communicator with experience influencing cross functional stakeholders Nice to Have: Experience working in early-stage, high-growth environments Familiarity with MLOps pipelines and integrating ML models into data workflows. Passionate about problem-solving with a proactive approach to finding innovative solutions. The expected salary for this role is $208,000 - $235,000 depending on experience and level