Aegistech
Job Description:
Our client in the insurance industry is seeking a full time/direct hire Machine Learning/GenAI Python engineer to join their AI/Data Science team. This position is hybrid onsite in lower Manhattan and is required to be onsite 3 days a week. Local candidates to NY Metro market only - no relocation.do
Machine Learning / GenAI Engineer (2-5 Years Experience)
Description Join our Artificial Intelligence Team (TRAIT) to build cutting-edge Machine Learning and Generative AI solutions used across our global organization. We're looking for a hands-on, early-career professional (2-5 years of experience) who has applied ML/AI techniques in a full-time, real-world setting-not just through academic or internship projects.
You'll be working on high-impact GenAI and LLM applications, developing end-to-end ML pipelines, and collaborating with domain experts to build intelligent solutions with measurable outcomes.
Key Responsibilities Develop, deploy, and maintain ML/AI models with an emphasis on LLMs, NLP, and RAG architectures Work with production-level ML systems including model development, evaluation (e.g. ROC), deployment, and fine-tuning Design and optimize data pipelines for ingesting, querying, and transforming large datasets Apply state-of-the-art GenAI frameworks and tooling, including Hugging Face, BERT, and fine-tuning transformer models Build and deploy cloud or local applications that interface with your ML models Collaborate cross-functionally with domain experts to ensure models are practically applicable to business problems Stay current on emerging technologies in GenAI, including GPU utilization, model safety, interpretability, and performance optimization Preferred Qualifications
2-5 years of full-time, hands-on experience building and deploying machine learning/ Gen AI solutions Strong Python programming skills, with proficiency in ML frameworks such as PyTorch, TensorFlow, and CUDA Practical experience working with LLMs and GenAI applications (fine-tuning, distillation, RAG, RLHF, etc.) Knowledge of NLP techniques, transformer-based architectures, and Hugging Face ecosystem Familiarity with model evaluation techniques (e.g., ROC curves), ensemble learning (stacking, boosting), and ML optimization methods Experience leveraging GPU-based computation for ML training/inference Solid grasp of ML best practices, version control, and scalable deployment approaches
Our client in the insurance industry is seeking a full time/direct hire Machine Learning/GenAI Python engineer to join their AI/Data Science team. This position is hybrid onsite in lower Manhattan and is required to be onsite 3 days a week. Local candidates to NY Metro market only - no relocation.do
Machine Learning / GenAI Engineer (2-5 Years Experience)
Description Join our Artificial Intelligence Team (TRAIT) to build cutting-edge Machine Learning and Generative AI solutions used across our global organization. We're looking for a hands-on, early-career professional (2-5 years of experience) who has applied ML/AI techniques in a full-time, real-world setting-not just through academic or internship projects.
You'll be working on high-impact GenAI and LLM applications, developing end-to-end ML pipelines, and collaborating with domain experts to build intelligent solutions with measurable outcomes.
Key Responsibilities Develop, deploy, and maintain ML/AI models with an emphasis on LLMs, NLP, and RAG architectures Work with production-level ML systems including model development, evaluation (e.g. ROC), deployment, and fine-tuning Design and optimize data pipelines for ingesting, querying, and transforming large datasets Apply state-of-the-art GenAI frameworks and tooling, including Hugging Face, BERT, and fine-tuning transformer models Build and deploy cloud or local applications that interface with your ML models Collaborate cross-functionally with domain experts to ensure models are practically applicable to business problems Stay current on emerging technologies in GenAI, including GPU utilization, model safety, interpretability, and performance optimization Preferred Qualifications
2-5 years of full-time, hands-on experience building and deploying machine learning/ Gen AI solutions Strong Python programming skills, with proficiency in ML frameworks such as PyTorch, TensorFlow, and CUDA Practical experience working with LLMs and GenAI applications (fine-tuning, distillation, RAG, RLHF, etc.) Knowledge of NLP techniques, transformer-based architectures, and Hugging Face ecosystem Familiarity with model evaluation techniques (e.g., ROC curves), ensemble learning (stacking, boosting), and ML optimization methods Experience leveraging GPU-based computation for ML training/inference Solid grasp of ML best practices, version control, and scalable deployment approaches