Perform performance evaluations of the LLM models, Implement LLMOps processes to run the end-to-end lifecycle of LLMs
Deploy, monitor , and maintain Machine Learning models and build AI Products in production environments, ensuring optimal performance and reliability.
Ensure high code quality, performance, and reliability through rigorous testing, code reviews, and adherence to software development best practices .
Drive innovation by researching and incorporating state-of-the-art machine learning techniques, tools, and frameworks into the platform .
Effective communication, listening, interpersonal, influencing, and alignment driving skills; able to convey important messages in a clear and compelling manner
Mentor team members, provide technical guidance, and foster a culture of collaboration, innovation, and continuous learning .

What do you need to bring

Qualifications

Masters / bachelor s in computer science, Computer engineering, Machine Learning, Data Mining, Information Systems, or related disciplines, with technical expertise in one or more of the above-mentioned areas or equivalent practical experience.
Strong background in deep learning techniques, particularly in NLP and Vision
Expertise in applying LLMs, prompt design, and fine-tuning methods
Strong proficiency in machine learning concepts, algorithms, and techniques, with hands-on experience in developing and deploying machine learning models.
Expert in multiple Programming/scripting languages, i.e., Python, Java, Scala , SQL , NoSQL (like HBase, Redis, Aerospike)
Good understanding of distributed systems, data streaming, complex event Processing, NoSQL s olutions for creating and managing data integration pipelines for batch and Real Time data needs.
Expertise in machine learning libraries/frameworks such as TensorFlow, PyTorch , scikit-learn, etc.
Experience with cloud platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes). Experience in Azure is a plus
Stay up to date with the latest advancements in AI/ML technology and industry trends and leverage this knowledge to enhance the platforms capabilities
Strong communication , listening, interpersonal, influencing, and alignment driving skills; able to convey important messages in a clear and compelling manner
Expertise in Big Data technologies such as Hadoop, Spark, HBase, Kafka.

Preferred

Prior experience in Content Understanding, enrichment, entity resolution or knowledge graph
Experience developing Gen AI applications/services for sophisticated business use cases and large amounts of unstructured data.
Strong background in MLOps and experimentation frameworks

Senior AI/ML Engineer, AI Solutions