As a Senior Data / ML Engineer, you'll join NVIDIA’s Digital Marketing platform team, dedicated to addressing our evolving data-driven marketing and compliance challenges. We value expertise in data science paired with a robust data engineering foundation. Together, we'll architect data pipelines, delve into advanced data analysis, and craft models using ML/AI. We seek someone proficient in programming and scripting for comprehensive data manipulation, analysis, and model creation. Our team thrives on working with Big Data technologies like Hadoop, Spark, and NoSQL databases, efficiently processing vast datasets. If you share a passion for innovation and creating exceptional experiences through the integration and management of large data sets, then you're the one we've been searching for! We believe in proactive problem-solving, minimal supervision, and being exceptional teammates who collaborate, think, and learn as one unit. Join us and let's make a difference together!What you’ll be doing:Architect solutions for complex data platforms, and large scale CI/CD data pipelines using a variety of technologies, relational and non-relational databases, and data warehouse solutions for data-driven marketing and compliance requirements.Responsible for end-to-end design and development, starting from requirements gathering with business and engineering partners to deployment to product systems using Agile development methodology.Develop and implement ML models: Design, develop, and deploy scalable machine learning models and algorithms that address complex business challenges in the marketing and business domain (e.g. build recommendation models for NVIDIA website). Apply various techniques such as supervised and unsupervised learning, deep learning, and reinforcement learning.Data pre-processing and analysis: Collaborate with data scientists and data engineers to collect, clean, pre-process, and transform large and wide datasets. Conduct exploratory data analysis (EDA) to uncover insights and identify patterns that boost the model performance.Model evaluation and optimization: Conduct detailed model evaluation metrics and validation to ensure accuracy, reliability, and scalability. Optimize model performance by fine-tuning hyper parameters, feature engineering, and applying techniques such as ensemble learning and continuous learning.Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure seamless deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies.Collaborate with multidisciplinary teams: Collaborate with product engineers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions. Provide technical guidance and mentorship to junior team members.What we need to see:Bachelors Degree in Computer Science or related field or equivalent experience.8+ years as data engineer, or related experience, in metadata management, and data quality, data retention, and data cleansing with exposure of defining data engineering solutions for emerging compliance requirements such as GDPR/CCPA/Data Localization.3 years of proven expertise as a Machine Learning Engineer or a similar role, with a consistent record of successfully delivering ML solutions.Advanced working SQL knowledge and experience working with relational / non-relational databases, schema design, and excellent SQL troubleshooting skills working with large datasets.Strong programming skills in languages such as Python, Golang, R, or Java. Experience with frameworks like TensorFlow, PyTorch, or scikit-learn.Proficiency in data manipulation, analysis, and visualization using tools like NumPy, pandas, and matplotlib.Deep understanding of machine learning algorithms, statistical models, and data structures.Familiarity with software development practices and version control systems (e.g., Git).Experience with experimental design, A/B testing, and evaluation metrics for ML models.Ways to stand out from the crowd:Architect level experience as a data engineer developing and deploying using Docker and Kubernetes on cloud technologies.Ability to analyze complicated and wide data sets, identify patterns, and derive significant insights.Demonstrated skills with AI/ML solutions for various applications, such as recommendation system, predictive analytics, and natural language processing.Self-motivated with a goal to stay updated on the latest methodologies and machine learning technologies.With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking people in the world working for us and, due to unprecedented growth, our business development teams are rapidly growing. If you're creative and autonomous with a real passion for you work, we want to hear from you.The base salary range is $160,000 - $247,250. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits.NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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