AI/ML Engineer

If so, then this AI/ML engineer role with a focus on generative AI might be the perfect fit for you!While prior experience in GenAI is not mandatory, a good understanding or knowledge of GenAI concepts and applications would be beneficial
Requirements Bachelors in Computer Science or equivalent degree 2 to 3 years of experience Must have strong analytical and problem-solving skills Strong foundations in Artificial Intelligence & Machine Learning concepts Personal project experience involving AI/ML technologies or applications would be highly advantageous Proven experience in designing, developing, and deploying machine learning models Familiarity with large language models (LLMs) and prompt engineering techniques Must have done projects in any of the following backend technologies: Python, Golang, NodeJS Understanding of deep learning frameworks (TensorFlow, PyTorch, etc) Experience with data manipulation libraries (pandas, NumPy) Strong foundation in engineering and programming concepts: Data structures and Algorithms, Object Oriented Programming, Databases, and System Design Good foundations in SQL, No-SQL, and Vector databases Bonus points for experience working with Google Cloud AI services such as Big QueryML, VertexAI, or Document AI offerings Good understanding of microservices, and RESTful API design Familiarity working with version control tools such as Bitbucket or Github Should be a goal-oriented individual with integrity and a continuous drive to learn and grow Responsibilities Collaborate with senior engineers to design and develop GenAI solutions on Google Cloud for client projects Prepare and pre-process data for model training, including data cleaning, feature engineering, and transformation Integrate generative AI models into production pipelines, monitoring their performance and making adjustments as needed Design and develop RAG-based systems for various applications (e-g , question answering, summarization, creative text generation) Participate in the testing, debugging, and optimization of GenAI applications Stay up-to-date on the latest advancements in generative AI models and techniques and identify opportunities to integrate them into existing products or develop entirely new ones Actively participate in an Agile-centric environment with team meetings, brainstorming sessions, and knowledge-sharing activities Act according to task prioritization and deliver on commitments with a sense of urgency Proactively learn about code and development best practices, take self-responsibility towards becoming an independent and reliable team member Actively seek feedback from their teammates and manager, and use the feedback as a tool for growth Document your work clearly and concisely for future reference and collaboration