Data Scientist

Robotics Technologies is hiring a Senior Data Scientist to support enterprise fintech artificial intelligence and machine learning initiatives, with a focus on Generative AI, LLMs, and foundation model development and deployment. This contract role is based onsite in Washington, DC.

Responsibilities

• Design, build, and optimize Generative AI, LLM, and multimodal foundation models for enterprise fintech applications.
• Fine-tune or adapt open-source and proprietary models to deliver high-performance solutions for NLP, document intelligence, anomaly detection, risk scoring, predictive analytics, and decisioning use cases.
• Lead experimentation to assess model accuracy, scalability, and fairness, and partner with engineering teams to deploy models on cloud-based ML pipelines (Azure, AWS) and data platforms (Databricks, Snowflake).
• Work with large-scale structured and unstructured datasets across the payments and financial ecosystem.
• Implement model monitoring, drift detection, and continuous retraining strategies.
• Evaluate and operationalize new AI technologies, foundation model architectures, responsible AI frameworks, and emerging research.
• Drive POCs and innovation initiatives that improve AI capabilities and support differentiation of products.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning, AI, or a related field.
• 5+ years of hands-on experience building and deploying machine learning models in production.
• Proven expertise with LLMs, transformer architectures, transfer learning, and model fine-tuning.
• Strong proficiency in Python, PyTorch or TensorFlow, and ML libraries such as Transformers.
• Experience with cloud ML platforms, containerization (Docker, Kubernetes), and MLOps tools.
• Solid understanding of statistical modeling, optimization, and evaluation methodologies.

Preferred Qualifications

• Experience in fintech, payments, banking, or fraud and risk environments.
• Background in vector databases, RAG pipelines, and knowledge graph integration.
• Experience with data privacy, model governance, and Responsible AI frameworks.
• Contributions to open-source AI/ML communities or research publications.

Technologies

• Python
• PyTorch
• TensorFlow
• Transformers
• LLMs
• Transformer architectures
• Transfer learning
• Docker
• Kubernetes
• Azure
• AWS
• Databricks
• Snowflake
• MLOps tools