
▷ High Salary: AI/ML Lead
3 days ago
About the Role
We are looking for an experienced AI/ML Lead to define and execute the AI/ML strategy, with a strong focus on developing and deploying advanced models tailored to insurance use cases. You will lead the model lifecycle end-to-end, integrate GenAI/LLM solutions, and ensure governance and compliance in a regulated industry.
This is a founding-level opportunity to:
- Shape the foundation of a next-gen insurtech platform.
- Collaborate with a highly motivated team tackling real-world, high-impact challenges.
- Design elegant, scalable systems that set new benchmarks for the industry.
- Drive meaningful innovation in a space that is ripe for disruption.
Key Responsibilities
- Define and drive the AI/ML strategy.
- Design and implement native model integration frameworks.
- Build scalable, objective-centric ML solutions for insurance applications (fraud detection, risk assessment, underwriting, claims automation).
- Lead end-to-end ML lifecycle management — data preprocessing, model training, deployment, monitoring, and optimization.
- Develop and fine-tune LLMs (GPT, Claude, LLaMA) with expertise in prompt engineering, RAG architectures, and evaluation frameworks.
- Integrate ML models with enterprise applications (Java/Spring) via REST APIs.
- Deploy and manage models in containerized environments (Kubernetes, Docker).
- Establish governance for responsible AI: bias detection, explainability (LIME/SHAP), fairness metrics, and regulatory compliance.
- Implement drift detection, automated monitoring, versioning, and A/B testing for continuous improvement.
Required Skills & Experience
- 6+ years of hands-on experience in ML engineering and model lifecycle management.
- Strong expertise in Python development (FastAPI, TensorFlow, PyTorch, Scikit-learn, XGBoost).
- Proficiency in ML model deployment, versioning, A/B testing, and Kubernetes containerization.
- Hands-on experience with document processing, OCR, NLP pipelines, and vector databases.
- Proven ability to build and optimize LLMs and Generative AI solutions (fine-tuning, quantization, model optimization).
- Familiarity with RAG pipelines, prompt engineering, and GenAI evaluation techniques.
- Deep knowledge of model governance, including explainable AI, fairness metrics, and bias detection.
- Experience in integrating ML solutions with enterprise systems.
Preferred Domain Expertise
- Insurance industry experience in:
- Fraud detection
- Risk assessment
- Underwriting models
- Claims automation
- AI regulatory compliance
What’s in it for You
- The chance to be part of a founding-level tech team.
- End-to-end ownership of AI/ML initiatives in a high-impact domain.
- Opportunities to work on cutting-edge Generative AI and ML solutions.
- A collaborative, high-growth environment where your work will create real-world impact.
- Competitive compensation and benefits.
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