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Tiger Analytics - Senior / Lead AI Engineer

Tiger Analytics - Senior / Lead AI Engineer

Tiger AnalyticsBangalore
30+ days ago
Job description

AI Lead - Generative AI & Machine Learning Engineering (MLE)

Experience : 7 to 13 years

Locations : Chennai, Bangalore, Hyderabad

Preference : Immediate joiners or Serving notice period

Job Description :

As an AI Lead specializing in Generative AI and Machine Learning Engineering (MLE) , you will be at the forefront of AI innovation. You will design, deploy, and operationalize sophisticated modelsincluding Large Language Models (LLMs) to solve complex business challenges. Collaborating with cross-functional teams, youll deliver scalable, production-ready AI solutions that drive intelligent automation and spark creativity across industries.

Key Responsibilities :

  • Generative AI, NLP & MLE : Design, develop, deploy, and scale cutting-edge applications leveraging Generative AI models (e.g., GPT, LLaMA, Mistral), NLP techniques, and MLE / MLOps best practices.
  • Model Customization & Fine-Tuning : Fine-tune and customize LLMs using techniques like LoRA and PEFT to create domain-specific, deployable models aligned with real-world business use cases.
  • ML Engineering & Deployment : Build and maintain end-to-end ML pipelinesincluding data preprocessing, model training, versioning, testing, and deploymentusing MLflow, Docker, Kubernetes, and CI / CD methodologies.
  • Innovative Problem Solving : Apply advanced AI and ML methodologies to solve practical business problems, delivering measurable impact.
  • Scalable AI Solutions : Collaborate with platform and data engineering teams to ensure robust model deployment, monitoring, and retraining in production environments.
  • Data-Driven Insights : Analyze structured and unstructured data to uncover trends, optimize model performance, and guide strategic decisions.
  • Cross-Functional Collaboration : Partner with Consulting, Engineering, and Platform teams to integrate AI / ML solutions into enterprise architectures and business strategies.
  • Client Engagement : Interact directly with clients to understand requirements, present customized AI solutions, and advise on the adoption and operationalization of Generative AI and ML technologies.

Required Skills and Expertise :

  • Experience : 6 - 9 years of hands-on experience with real-world projects in Generative AI and Machine Learning Engineering (MLE / MLOps).
  • Generative AI Expertise : Deep expertise in designing and deploying LLM-based solutions using frameworks like HuggingFace, LangChain, Transformers, etc.
  • MLE & Production Readiness : Proven track record of building scalable, reliable, production-grade ML models and pipelines.
  • Deployment & Best Practices : Hands-on experience with containerization (Docker), orchestration (Kubernetes), model tracking (MLflow), and deployment on cloud platforms (AWS, GCP, Azure).
  • Development Proficiency : Strong coding skills in Python, with experience using web frameworks like Django or Flask.
  • API & Cloud Architecture : Deep understanding of APIs, microservices, and cloud-native deployment strategies.
  • Innovation & Curiosity : A strong passion for staying up to date with the latest advancements in Generative AI, LLMs, and ML engineering.
  • Communication : Ability to translate complex technical concepts into clear, business-focused insights and actionable recommendations.
  • ref : hirist.tech)

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