Lead the engineering and deployment of AI enablement capabilities for Finance teams, including end-user use cases and production AI/ML systems.

Work with cross-functional partners including engineers, data scientists, product managers, and designers to deliver AI-powered products for associates and customers.
Design, develop, test, deploy, and support AI software components using machine learning models, including model evaluation and experimentation.
Build and operate large language model inference features, similarity search, guardrails, governance, observability, and agentic AI capabilities.
Fine-tune, develop, and evaluate machine learning models and foundation models.
Contribute within a cross-functional Agile team to create and enhance software leveraging state-of-the-art AI and ML capabilities.
Provide technical vision and thought leadership to shape the long-term roadmap for pioneering AI systems.
Apply a broad mix of Open Source and SaaS AI technologies.
Use knowledge of ML modeling techniques and common issues to inform ML infrastructure decisions.
Retrain, maintain, and monitor models in production.
Build optimized data pipelines to supply training and inference datasets for ML models.
Maintain code quality to reduce vulnerabilities, ensure responsible governance from a risk perspective, and follow best practices for Responsible and Explainable AI.

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

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 building production-ready data pipelines that feed ML models
3+ years on-the-job experience with an industry-recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow
3+ years developing AI and 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 their performance
Experience leveraging interactive AI tooling to accelerate productivity, using capabilities beyond basic code completion
Experience deploying scalable AI/ML solutions in a public cloud such as AWS Bedrock, Google Cloud, or Azure

USD 197,300 - 225,100 per year
Salary ranges by location:
- Cambridge, MA: $197,300 - $225,100
- McLean, VA: $197,300 - $225,100
- New York, NY: $215,200 - $245,600
Candidates hired in other locations are subject to the pay range for that location, and the actual annualized salary offered is reflected in the candidate’s offer letter.

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

Lead Machine Learning Engineer

Job Description