AI/ML Engineer

  • Reston, VA
  • Posted 2 days ago | Updated 5 hours ago

Overview

On Site
Accepts corp to corp applications
Contract - Long Term

Skills

AI/ML Engineer

Job Details

Need someone with strong experience in Python development, recent experience with AI/ML, and AWS. 8+ years Minimum

Position Summary:

Title: Developer IV

Duration: 12 Months Long Term

Location: Reston Town Center, VA 20190

Hybrid Onsite: 3 Days per week from Day1

Experience:

  • 8+ years overall in Software Engineering disciplines, preferably in the financial services industry
  • 2-3 years of experience in AI/ML engineering roles
  • Strong programming skills in Python, SQL and experience with AWS.

Key Responsibilities:

  • Design, test, and refine prompts for large language models (LLMs) to support financial reporting, summarization, and client communication tools.
  • Analyze structured and unstructured financial data using Python and SQL, delivering insights through dashboards and reports.
  • Develop and maintain data pipelines and ETL workflows to support GenAI model training and evaluation.
  • Use AWS SageMaker to build, train, and deploy machine learning and GenAI models.
  • Collaborate with data scientists, analysts, and business stakeholders to align AI solutions with financial objectives.
  • Monitor model performance and iterate on prompt and model design to improve accuracy and relevance.
  • Document workflows, models, and prompt strategies for internal knowledge sharing and compliance.

Required Qualifications:

  • 2 3 years of experience in data analysis or machine learning roles.
  • Proficiency in Python and SQL for data manipulation and analysis.
  • Hands-on experience with major AWS services, particularly SageMaker, S3, Redshift, and Lambda.
  • Experience working with LLMs (Anthropic Claude, Sonnet) and prompt engineering techniques.
  • Strong understanding of financial data, KPIs, and reporting standards.
  • Excellent communication and collaboration skills.

Preferred Qualifications:

  • Experience in the finance or fintech industry.
  • Familiarity with vector databases (e.g., FAISS, Pinecone) and retrieval-augmented generation (RAG).
  • Exposure to data visualization tools (e.g., Power BI, Tableau).
  • Understanding of MLOps practices and model lifecycle management.

Education

  • Bachelor's degree in computer science, Data Science, Finance, or a related field.
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