Data Scientist

Quantum Technologies. LLC; Washington (District of Columbia); On-site; USD 120,000 - 180,000; Full time

Job summary

Quantum Technologies LLC is seeking a senior AI/ML engineer to design, build, and optimize Generative AI and multimodal models for enterprise fintech applications. You will fine-tune models, develop NLP and risk analytics solutions, and integrate in cloud ML pipelines across Azure and AWS.

You will lead experiments, monitor model performance, and collaborate with data engineers on Databricks and Snowflake deployments, applying responsible AI practices and cutting-edge research.

Qualifications

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

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. Build high-performance models for NLP, document intelligence, anomaly detection, risk scoring, predictive analytics, and decisioning use cases.
• Lead experimentation to evaluate model accuracy, scalability, and fairness. Partner with engineering teams to deploy models on cloud-based ML pipelines (Azure, AWS) & 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 enhance AI capabilities and differentiate our products.

Skills

Python

PyTorch/TensorFlow

Transformers

Cloud ML platforms

Docker/Kubernetes

ML libraries

Education

Bachelor’s or Master’s in CS/DS/ML/AI

Tools

Databricks

Snowflake

Job description

Key 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 Build high-performance models for NLP, document intelligence, anomaly detection, risk scoring, predictive analytics, and decisioning use cases.
• Lead experimentation to evaluate model accuracy, scalability, and fairness. Partner with engineering teams to deploy models on cloud-based ML pipelines (Azure, AWS) & 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 enhance AI capabilities and differentiate our products.

Required Qualifications:

• Bachelors or Masters in Computer Science, Data Science, Machine Learning, AI, or 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 working in fintech, payments, banking, or fraud/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.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.