Data Science Researcher - NiCE

Developing end-to-end ML systems, tailored to specific project needs, to train and serve production-level models in a high-stakes environment. Deploying GenAI and agentic AI systems to customers in production, improving on existing solutions or creating new services from scratch. Designing and building agentic AI flows - tool use, multi-step reasoning, and orchestration. Forecasting work volume and optimizing shift schedules using time-series methods and mathematical optimization. Integrating new features and solutions into large existing software systems, stringing multiple disciplines together. Running unstructured evaluation processes - finding noteworthy phenomena, experimenting, and feeding conclusions back to the team. Owning projects end-to-end, leading team members and colleagues to efficient planning and delivery. 5+ years of experience as an applied researcher or research engineer. Loves reading and writing code. Hands-on Python developer - training models, using trained models, data carpentry, preprocessing and analysis. Hands-on with PyTorch. ML-Ops and cloud experience - deploying and serving models on AWS or another cloud provider. Experience with mathematical optimization (e.g. Gurobi). Hands-on experience designing and building agentic AI flows. Effective Claude user. Independent and analytical thinker - capable of running unstructured evaluations and driving conclusions. Experience working in an agile environment. MSc in Computer Science or an equivalent engineering field. Experience with HuggingFace, scikit-learn, and pandas/SQL. Containerization with Docker. LLM-specific experience: RAG, fine-tuning, evaluation frameworks.

Developing end-to-end ML systems, tailored to specific project needs, to train and serve production-level models in a high-stakes environment. Deploying GenAI and agentic AI systems to customers in production, improving on existing solutions or creating new services from scratch. Designing and building agentic AI flows - tool use, multi-step reasoning, and orchestration. Forecasting work volume and optimizing shift schedules using time-series methods and mathematical optimization. Integrating new features and solutions into large existing software systems, stringing multiple disciplines together. Running unstructured evaluation processes - finding noteworthy phenomena, experimenting, and feeding conclusions back to the team. Owning projects end-to-end, leading team members and colleagues to efficient planning and delivery. 5+ years of experience as an applied researcher or research engineer. Loves reading and writing code. Hands-on Python developer - training models, using trained models, data carpentry, preprocessing and analysis. Hands-on with PyTorch. ML-Ops and cloud experience - deploying and serving models on AWS or another cloud provider. Experience with mathematical optimization (e.g. Gurobi). Hands-on experience designing and building agentic AI flows. Effective Claude user. Independent and analytical thinker - capable of running unstructured evaluations and driving conclusions. Experience working in an agile environment. MSc in Computer Science or an equivalent engineering field. Experience with HuggingFace, scikit-learn, and pandas/SQL. Containerization with Docker. LLM-specific experience: RAG, fine-tuning, evaluation frameworks.

Developing end-to-end ML systems, tailored to specific project needs, to train and serve production-level models in a high-stakes environment. Deploying GenAI and agentic AI systems to customers in production, improving on existing solutions or creating new services from scratch. Designing and building agentic AI flows - tool use, multi-step reasoning, and orchestration. Forecasting work volume and optimizing shift schedules using time-series methods and mathematical optimization. Integrating new features and solutions into large existing software systems, stringing multiple disciplines together. Running unstructured evaluation processes - finding noteworthy phenomena, experimenting, and feeding conclusions back to the team. Owning projects end-to-end, leading team members and colleagues to efficient planning and delivery. 5+ years of experience as an applied researcher or research engineer. Loves reading and writing code. Hands-on Python developer - training models, using trained models, data carpentry, preprocessing and analysis. Hands-on with PyTorch. ML-Ops and cloud experience - deploying and serving models on AWS or another cloud provider. Experience with mathematical optimization (e.g. Gurobi). Hands-on experience designing and building agentic AI flows. Effective Claude user. Independent and analytical thinker - capable of running unstructured evaluations and driving conclusions. Experience working in an agile environment. MSc in Computer Science or an equivalent engineering field. Experience with HuggingFace, scikit-learn, and pandas/SQL. Containerization with Docker. LLM-specific experience: RAG, fine-tuning, evaluation frameworks.