AI/ML Lead
2 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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