- Perform performance evaluations of the LLM models, ImplementLLMOpsprocesses to run the end-to-end lifecycle of LLMs
- Deploy,monitor, andmaintainMachine Learning models and build AI Products in production environments, ensuringoptimalperformance 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 incorporatingstate-of-the-artmachine 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,providetechnical 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 technicalexpertisein one or more of the above-mentioned areas or equivalent practical experience.
- Strong background in deep learning techniques, particularly in NLP and Vision
- Expertisein applying LLMs, prompt design, and fine-tuning methods
- Strongproficiencyin 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,NoSQLsolutions for creating and managing data integration pipelines for batch and Real Time data needs.
- Expertisein 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 andleveragethis 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
- Expertisein 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 andlarge amountsof unstructured data.
- Strong background in MLOps and experimentation frameworks
