AI/ML Solutions Architect

22 hours ago

Madurai, Tamil Nadu, India beBeeData Full time US$ 1,60,000 - US$ 2,00,000

We are seeking a highly skilled Data Science professional to lead our team's AI/ML initiatives. This role combines technical expertise with exceptional client relationship skills to drive business outcomes.

Key Responsibilities
  • Serve as primary technical contact for enterprise clients, building trusted relationships with stakeholders from technical teams to C-level executives.
  • Architect end-to-end ML solutions, including predictive models, recommendation systems, and generative AI applications tailored to customer use cases.
  • Lead proof-of-concepts, pilot deployments, and production implementations while ensuring seamless integration with customer systems.
  • Conduct data assessments, provide ML strategy recommendations, and guide customers through model lifecycle management.
  • Mentor customer teams and build internal data science capabilities through training and best practices sharing.
  • Gather customer feedback to enhance existing solutions and identify new product opportunities.
Required QualificationsEducation & Experience
  • Master's in Data Science, Computer Science, Statistics, or a related quantitative field.
  • 5+ years hands-on data science experience with 2+ years in customer-facing or consulting roles.
  • Proven track record delivering ML solutions in production environments.
Technical Skills
  • Programming: Advanced Python/R, strong SQL capabilities.
  • ML Expertise: Deep learning, NLP, traditional ML algorithms, and generative AI/LLMs.
  • Frameworks: TensorFlow, PyTorch, scikit-learn, cloud ML services (AWS/Azure/GCP).
  • Tools: MLOps platforms, data visualization tools, big data technologies.
Business Skills
  • Exceptional communication and presentation abilities for technical and non-technical audiences.
  • Strong project management and stakeholder relationship skills.
  • Customer-centric problem-solving mindset.
  • Ability to translate business requirements into technical solutions.
Success Metrics
  • Customer satisfaction and retention rates.
  • Successful ML solution deployments from concept to production.
  • Revenue growth within assigned accounts.
  • Effective knowledge transfer and capability building.

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