Senior Lead AI/ML Engineer - R01573662

Brillio 2
Bangalore +1 more
On-site

Who this role is best for

Aimed at senior conversational AI specialists who can design and optimize dialogue systems.

Best fit for

  • Candidates with 5-8 years in data science and 2 years in conversational AI technologies
    — “at least 5-8 years of experience in data science, including 2 years specifically in conversational AI technologies”
  • Individuals who have worked with multiple conversational AI platforms like RASA, Google Dialog Flow, and IBM Watson
    — “Utilize platforms such as RASA, Kore.ai, Google Dialog Flow, and IBM Watson to build and refine conversational agents”

Things to consider

  • The role requires a specific focus on conversational AI over general data science
    — “Specialization: Conversational AI: Senior Data Scientist”
  • Candidates must be prepared to work with agentic AI development and deployment
    — “Collaborate with engineering and product teams to define AI deployment paths and integrate agentic AI solutions into production environments”

How to stand out

  • Demonstrate experience in AI testing and model optimization with specific platforms like RASA and Spark NLP
    — “Design and execute functional and AI quality testing, including grounding, unsupported-response, contradiction, and scenario validation”
  • Highlight your ability to build governance frameworks for conversational AI systems
    — “Implement governance frameworks for conversational AI to maintain compliance and quality standards”
  • Showcase your expertise in both NLU and NLG, especially in the context of dialogue design
    — “Experience with dialogue design for conversational AI platforms”
  • Emphasize your knowledge of reinforcement learning and syntax/semantic analysis techniques
    — “Develop and optimize AI models for dialogue management, syntax and semantic analysis, and reinforcement learning”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • ensure accuracy and relevance in conversational AI applications
  • develop and optimize AI models
  • collaborate with engineering and product teams
  • implement governance frameworks
  • build and refine conversational agents
Typical background
data scienceconversational AI technologiesagentic AI development

Skills & requirements

Required

Conversational AIReinforcement LearningText ClassificationNatural Language UnderstandingDialogue ManagementAI Quality TestingGovernance FrameworksAgentic AI DevelopmentAI DeploymentAdvanced Text ClassificationSyntax And Semantic AnalysisDialogue Design

Preferred

Automatic Speech RecognitionNatural Language GenerationSpark NLPRecurrent Neural NetworksConversational AI Testing MethodologiesScenario Validation

Stack & domain

Dialogue DesignSyntax And Semantic AnalysisReinforcement LearningText ClassificationGovernance For Conversational AIRASANatural Language Understanding (nlu)Kore.aiGDF (google Dialog Flow)IBM WatsonAutomatic Speech Recognition (asr)Dialogue Management (nlg)Spark NLPRecurrent Neural NetworksConv AI TestingCollaborationProblem-solvingCommunicationTeamworkTime ManagementOrganizational SkillsStrategic ThinkingAdaptabilityMachine LearningNatural Language ProcessingConversational AIAIMLData Science

About the role

Original posting from Brillio 2 via Lever

Senior Lead AI/ML Engineer

Primary Skills:

  • Dialogue Design, Syntax and semantic analysis, Reinforcement learning, Text Classification, Governance for Conversational AI, RASA, Natural Language Understanding (NLU), Kore.ai, GDF (Google Dialog Flow), IBM Watson, Automatic Speech Recognition (ASR), Dialogue Management (NLG), Spark NLP, Recurrent Neural Networks, Conv AI Testing

Specialization:

  • Conversational AI: Senior Data Scientist

Job requirements:

  • Experience Range: With at least 5-8 years of experience in data science, including 2 years specifically in conversational AI technologies and agentic AI development Key Responsibilities: 1. Evaluate agent output results and EVal tests to ensure accuracy and relevance in conversational AI applications 2. Design and execute functional and AI quality testing, including grounding, unsupported-response, contradiction, and scenario validation 3. Develop and optimize AI models for dialogue management, syntax and semantic analysis, and reinforcement learning 4. Collaborate with engineering and product teams to define AI deployment paths and integrate agentic AI solutions into production environments 5. Implement governance frameworks for conversational AI to maintain compliance and quality standards 6. Utilize platforms such as RASA, Kore.ai, Google Dialog Flow, and IBM Watson to build and refine conversational agents 7. Apply advanced text classification and natural language understanding techniques to enhance AI translation and conversation capabilities 8. Conduct scenario-based validation and troubleshooting to continuously improve conversational AI performance Required Skills: 1. Hands-on experience with RASA 2. Proficiency with Natural Language Understanding (NLU) 3. Experience with Google Dialog Flow 4. Working knowledge of Kore.ai 5. Familiarity with IBM Watson for conversational AI 6. Strong proficiency in syntax and semantic analysis using Python or relevant libraries 7. Experience with reinforcement learning algorithms (e.g., Q-learning, policy gradients) 8. Advanced text classification techniques (e.g., transformers, BERT, LSTM) 9. Experience in dialogue design for conversational AI platforms Preferred Skills: 1. Experience with Automatic Speech Recognition (ASR) integration 2. Advanced skills in Natural Language Generation (NLG) 3. Proficiency in Spark NLP for text processing 4. Hands-on experience with Recurrent Neural Networks (RNNs) 5. Background in conversational AI testing methodologies and scenario validation Desired Qualifications: 1. Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Information Technology, or a closely related discipline 2. Certification in Machine Learning, Natural Language Processing, or Conversational AI from recognized institutions 3. Relevant certification in conversational AI platforms such as RASA or Google Dialog Flow

Source: Brillio 2 careers (Lever)

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