
ML Data Scientist
4 days ago
As MP&S DevOps Org, we are committed to continuous learning and delivering solutions on a global scale. By working with a diverse range of multi-functional teams, we are able to combine the best of our expertise to create interactive experiences with a skilled group of software engineers. We thoroughly enjoy the process
You will lead the machine learning project lifecycle, design virtual assistants, and develop advanced analytics to drive innovation and solve business challenges with AIOps expertise.
Description
As an ML Engineer, you will oversee the machine learning project lifecycle, employing best practices and optimally managing software delivery. You will lead the design and development of virtual assistants utilizing Conversational AI platforms, fostering innovative concepts for impactful solutions. You will design and develop advanced analytic solutions across diverse functional areas, collaborating with business stakeholders to identify AI/ML challenges and capitalize on LLM technologies. You will provide technical support on LLM and GenAI usage, assist teams in adhering to best practices, and lead AIOps projects, prioritizing clustering, classification, anomaly detection, and capacity prediction. Proficiency in understanding requirements, designing conversational flows, and developing intent and entities for chatbots is crucial.
Minimum Qualifications
5-7 years of experience implementing AI/ML models in enterprise systems.
Deep understanding of AI/ML concepts, including supervised and unsupervised learning, deep learning, anomaly detection, and large language models.
Expertise in Python and relevant libraries and frameworks (e.g., Pandas, Numpy, TensorFlow).
Relevant experience in designing, developing, and deploying conversational bots.
Experience working with Prometheus, Splunk, Datadog, and Grafana.
Experience in NLP, NLU, ML, and Conversational AI.
Expertise in seamlessly integrating bot systems with backend systems, databases, and APIs for smooth data exchange and interactions.
Excellent troubleshooting and analytical skills in a complex, distributed environment.
Excellent communication, presentation, and collaboration skills.
Self-starter, capable of working independently.
Preferred Qualifications
BS or MS in Engineering, Computer Science, or a related field.
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