Immediate need for a talented Senior Data Scientist . This is a 06+months contract opportunity with long-term potential and is located in McLean, VA(Onsite). Please review the job description below and contact me ASAP if you are interested.
Job ID:26-35510
Pay Range: $80 - $85/hour. Employee benefits include, but are not limited to, health insurance (medical, dental, vision), 401(k) plan, and paid sick leave (depending on work location).
Key Responsibilities:
- Architect and implement scalable AI Agents and GenAI applications for complex business use cases.
- Develop and evaluate LLMs (e.g., Claude, Azure OpenAI, open-source models).
- Fine-tune open weight models and design systems using vector databases and knowledge bases.
- Curate enterprise data with connectors integrated into AWS Bedrock Knowledge Base/Elastic.
- Implement Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication.
- Build and maintain Jupyter notebooks on platforms like SageMaker, MLFlow, and Kubeflow (on Kubernetes/EKS).
- Integrate GenAI solutions with enterprise platforms via APIs and standardized GenAI patterns.
- Establish validation procedures using Evaluation Frameworks (DeepEval), bias mitigation, safety protocols, and guardrails.
- Design robust ingestion pipelines for data extraction, chunking, enrichment, and anonymization.
- Orchestrate multimodal pipelines with scalable frameworks (e.g., Apache Spark, PySpark) for automated ETL/ELT workflows.
- Implement embedding-driven workflows, mapping media content to vector representations and integrating with vector stores (AWS KnowledgeBase/Elastic/Mongo Atlas).
Key Requirements and Technology Experience:
- 5+ years of proven experience as an Applied AI Engineer with deep expertise in modern AI workflows and GenAI application design.
- Bachelor’s degree in Computer Science, Data Science, AI/ML, or related technical field (Master’s preferred).
- Advanced proficiency in Python, big data technologies (e.g., Spark, Hadoop), and data manipulation libraries (e.g., Pandas, NumPy).
- Solid knowledge of classical ML algorithms, deep learning architectures, LLMs, generative AI, and reinforcement learning.
- Hands-on experience with Microsoft Azure, Azure OpenAI, and AWS cloud platforms.
- Strong understanding of Spec-Based Development, Git, and CI/CD best practices.
- Expertise in prompt engineering, vector databases (AWS KnowledgeBase/Elastic), and multimodal models.
- Proven experience with cloud-native AI development (AWS SageMaker, Bedrock, MLFlow on EKS).
- Strong programming skills in Python and ML libraries (Transformers, LangChain, etc.).
- Deep understanding of GenAI architectural patterns and Evaluation Frameworks (DeepEval).
- Demonstrated ability to work in cross-functional agile teams.
- GitHub Code Repository Link required for each candidate. Thorough vetting is mandatory.
- Experience in financial, regulatory technology, or enterprise automation.
- Familiarity with MLOps tools (MLflow, Kubeflow, Weights & Biases).
- Contributions to open-source AI projects or research publications.
- Experience with containerization and orchestration (Docker, Kubernetes).
- Experience with Spark is optional but preferred.
Our client is a leading Banking And Financial Industry, and we are currently interviewing to fill this and other similar contract positions. If you are interested in this position, please apply online for immediate consideration.
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