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Chase Robotics and Ai
AI Engineer
Career Insights for Generative Artificial Intelligence Engineer
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What they do
A Generative Artificial Intelligence Engineer develops, designs, and manages generative models and algorithms that support the generation of new content in the form of images, text, audio, and other multimedia. They utilize GPTs, GANs, VAEs, and other deep learning architectures to craft systems capable of generating data. May work with data scientists, machine learning engineers, and software developers.
$166,830 / year median in California
Job Description
Overview Join our innovative team as an AI Engineer and be at the forefront of developing cutting-edge artificial intelligence solutions that transform data into actionable insights. In this role, you will design, build, and deploy advanced AI models and machine learning frameworks to solve complex business challenges. Your expertise will drive the implementation of scalable AI systems, leveraging big data technologies and cloud services to deliver impactful results. We are seeking passionate professionals eager to push the boundaries of AI and contribute to pioneering research and development initiatives. Responsibilities Develop, train, and evaluate machine learning models utilizing frameworks such as TensorFlow, ensuring high accuracy and efficiency for diverse applications. Design and implement scalable big data systems using tools like Hadoop, Spark, and ETL processes to manage large datasets effectively. Apply statistical modeling and analysis techniques using tools such as R, SAS, and statistical analysis software to extract meaningful insights from complex data. Integrate AI models into production environments through model deployment strategies, ensuring robustness and scalability across cloud platforms like AWS. Collaborate with cross-functional teams to develop natural language processing (NLP) applications and generative AI solutions that enhance user engagement. Conduct model training sessions focusing on predictive modeling analysis, model evaluation, and continuous improvement cycles. Utilize SQL databases, data mining techniques, and database design principles to optimize data storage and retrieval for analytics purposes. Experience Proven experience in machine learning/AI-based analysis with a strong understanding of AI implementation in real-world scenarios. Hands-on expertise with machine learning frameworks such as TensorFlow, Spark MLlib, or similar tools. Familiarity with big data systems including Hadoop ecosystem components (HDFS, MapReduce) and Spark implementation for large-scale data processing. Proficiency in programming languages including Python, Java, C, VBA, Bash (Unix shell), with additional knowledge of SQL for database management. Experience with cloud-based machine learning services on platforms like AWS or similar providers is highly desirable. Knowledge of natural language processing (NLP), predictive modeling analysis, statistical analysis tools, and model evaluation techniques. Understanding of data analytics workflows involving data mining, data integration (Talend), Looker for visualization, and data scalability considerations. Embark on a career where your skills in AI engineering will shape the future of intelligent systems! We foster an environment of innovation where your contributions directly impact technological advancements across industries.