Lead Machine Learning Engineer

Lead the delivery of AI enablement for Finance, building and governing ML systems and end user AI capabilities.

Responsibilities

• Partner with engineers, data scientists, product managers, and designers to deliver AI-powered products that support associate workflows and customer value
• Design, develop, test, deploy, and support AI software components using machine learning, including:
  • Model evaluation and experimentation
  • Large language model inference
  • Similarity search
  • Guardrails
  • Governance and risk-aligned controls
  • Observability
  • Agentic AI
• Fine-tune, develop, and evaluate machine learning and foundation models
• Collaborate on a cross-functional Agile team to create and improve software using state-of-the-art AI and ML capabilities
• Contribute technical vision and thought leadership to guide the long-term roadmap for pioneering AI systems
• Use a broad stack of open source and SaaS AI technologies
• Apply expertise in ML modeling techniques and related issues to inform ML infrastructure decisions
• Retrain, maintain, and monitor models in production
• Build optimized data pipelines to support ML model training and performance
• Manage code to reduce vulnerabilities, ensure model governance from a risk perspective, and follow best practices for Responsible and Explainable AI

Requirements

• Bachelor’s Degree
• At least 6 years of experience designing and building data-intensive solutions using distributed computing (internship experience does not apply)
• At least 4 years of experience programming with Python, Scala, or Java
• At least 2 years of experience building, scaling, and optimizing ML systems

Preferred Qualifications

• Master’s or Doctoral Degree in computer science, electrical engineering, mathematics, or a similar field
• 7+ years of experience designing, developing, delivering, and supporting AI services at scale
• 3+ years of experience building production-ready data pipelines that feed ML models
• 3+ years of on-the-job experience with an industry-recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
• 3+ years of experience developing AI/ML algorithms or technologies using Python
• 2+ years of experience with Retrieval Augmented Generation (RAG)
• 2+ years of experience with data gathering and preparation for ML models
• 2+ years of people leader experience
• 1+ years of experience leading teams developing ML solutions using industry best practices, patterns, and automation
• Experience designing, implementing, and scaling complex data pipelines for ML models and evaluating performance
• Experience leveraging interactive AI tooling to accelerate productivity beyond basic code completion
• Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, or Azure

Technology Stack

• Python
• Scala
• Java
• scikit-learn
• PyTorch
• Dask
• Spark
• TensorFlow
• Retrieval Augmented Generation (RAG)
• AWS Bedrock
• Google Cloud
• Azure

Benefits

• Eligible for performance-based incentive compensation, which may include cash bonus(es) and/or long-term incentives (LTI)
• Comprehensive, competitive, and inclusive health, financial, and other benefits supporting total well-being

Location

• McLean, VA 22101 (onsite)

Salary

• USD 197,300 - 225,100 per year
• Cambridge, MA: $197,300 - $225,100
• McLean, VA: $197,300 - $225,100
• New York, NY: $215,200 - $245,600

Candidates hired in other locations will be subject to the pay range for that location, and the annualized salary offered will be reflected in the candidate’s offer letter.