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TransRe

engineering opportunity

Machine Learning Engineer

Develop and scale machine learning models, including data pipeline construction and the implementation of LLM and GenAI applications. Collaborate with reinsurance domain experts to improve predictive capabilities and manage the overall ML modeling ecosystem.

New York, New York, United StateshybridFULL_TIME

Posted

About the role

What will you do at TransRe?

About Us Since 1977 we have delivered first class solutions to insurers worldwide, by combining global reach with local decision making. We have built customer & broker relationships on years of trust, experience and execution. Through our people, our products and our partnerships, we deliver the capacity and expertise necessary to contribute to the sustainable growth of prosperous communities worldwide.

To do so, our colleagues work with: Integrity Work honestly, to enhance TransRe’s reputation Respect Value all colleagues. Collaborate actively. Performance We reward excellence.

Be accountable, manage risk and deliver TransRe’s strengths Entrepreneurship Seize opportunities. Innovate for and with customers. Customer Focus Anticipate their priorities.

Exceed their expectations. We have the following job opportunity in our New York City office:

Description

This role will be part of our TransRe Artificial Intelligent Team (TRAIT) and will be responsible for providing key Machine Learning deliverables to our global user base.

Responsibilities

  • include, but are not limited to: Constructing machine learning models including data collection, normalization, and standardization, data pipeline construction, model selection and hyperparameter tuning, working ml systems that can add new data into ml model Working on and researching the most recent LLM and GenAI models, safety, interpretability, and applications Creating apps to present ml models and host them in the cloud or locally Creating pipelines to query and retrieve and update data for existing applications to keep them updated Supervising the scaling and management of the machine learning modeling ecosystem Finding orthogonal data sets to supplement models and increase alpha Staying abreast of new technology and machine learning methodologies and implementing them into the model building architecture Working alongside (re)insurance domain experts to improve predictive aspects of their lines of business Requirements As an ideal candidate, you will possess the following skills and knowledge: Proven track record of building, scaling and productizing multiple machine learning models Strong experience in the full life-cycle of machine learning models from initial theorizing to final implementation & support High proficiency with working with LLMs- fine-tuning, RLHF, distillation, optimization Experience working with sparse, high dimensional, tabular, and time series data Python ml stack PyTorch, TensorFlow, CUDA Boosting and bagging algorithms ML Optimization Techniques Ensemble Stacking and Meta Learners Work Schedule TransRe is supportive of an agile work schedule, which may differ based on individual roles, your local office’s practices and preferences, marketplace trends, and TransRe’s business objectives.
  • This position is eligible for a hybrid work schedule with 3 days in the office per week, and 2 days remote.

Compensation

In addition to base salary, for this position, TransRe offers a comprehensive benefits package, paid time off, and incentive pay opportunity. The anticipated annual base salary range in New York for this position, exclusive of benefits, paid time off, and incentive pay opportunity is $145,000 – $170,000. This range is an estimate and the actual base salary offered for this position will be determined based on certain factors, including the applicant’s specific skill set and level of experience.

We are an Equal Opportunity Employer (EOE) and we support diversity in the workforce.

TransRe is an equal opportunity employer and will consider all applicants without regard to race, color, religion or creed, national origin, ancestry, sex, disability, medical condition, genetic information, age, sexual orientation, gender, gender identity or expression, marital or partnership status, familial status, caregiver status, military service or veteran status, or any other status protected by applicable federal, state or local law.

Which skills does this role require?

Machine LearningLLMsGenAIPythonPyTorchTensorFlowCUDAFine-tuningRLHFDistillationOptimizationBoosting and BaggingEnsemble StackingMeta LearnersData Pipeline ConstructionCloud HostingLLMBoostingBaggingData NormalizationHyperparameter TuningCloud ComputingReinsurancePredictive ModelingTime Series DataTabular DataHigh Dimensional DataData PipelinesModel InterpretabilityModel SafetyAlpha GenerationAgile

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