ML Data Scientist

Responsibilities

    AI-Powered Solutions: Drive the complete machine learning project lifecycle, ensuring best practices and detailed software delivery.
    Intelligent Assistants: Lead the design and development of virtual assistants using Conversational AI platforms, creating impactful and intuitive experiences.     Data-Driven Insights: Collaborate with business stakeholders to identify AI/ML opportunities and develop advanced analytic solutions leveraging LLM technologies, redefining data into actionable strategies.

Minimum Qualifications

    Experience: 3+ years of hands-on experience implementing AI/ML models in enterprise systems.
    Deep understanding of core AI/ML concepts, including supervised/unsupervised learning, deep learning, and anomaly detection.     Proven expertise in generative AI principles and applications, with a strong understanding of LLM architectures and fine-tuning techniques.     Mastery of Python and key AI/ML libraries/frameworks (Pandas, NumPy, TensorFlow, PyTorch, etc.). Demonstrated ability to develop and deploy production-ready solutions using GenAI models.     Extensive experience designing, developing, and deploying sophisticated conversational bots, including intent recognition, dialogue management, and natural language generation.     Hands-on experience building and deploying solutions utilising multi-modal models and Graph RAG pipelines. Familiarity with RAG benchmarking frameworks and evaluation methodologies.     Core AI/ML Competencies: Deep expertise in NLP, NLU, ML, and Conversational AI.     Proven track record to seamlessly integrate bot systems with backend systems, databases, and APIs to create end-to-end solutions.     BS or MS in Engineering, Computer Science, or a related field.

Preferred Qualifications

    Demonstrated experience in designing, building, and deploying AI/ML platforms and services at scale. A track record of developing solutions that can handle high volumes of data and traffic.
    Exceptional troubleshooting and analytical skills, with the ability to diagnose and resolve complex issues in distributed environments.     Excellent communication, presentation, and collaboration skills, with the ability to effectively communicate technical concepts to both technical and non-technical audiences.     A proactive and independent mindset, with a strong desire to learn and a proven track record to thrive in a fast-paced, multifaceted environment.