Director, Machine Learning Engineer

In McLean, VA, this Director-level Machine Learning Engineering role focuses on leading large-scale machine learning initiatives for financial services. The position emphasizes building production-ready ML models and the software and data systems that support them, with strong engineering leadership alongside hands-on technical work.

As part of the Information Technology Senior Management Forum, you will collaborate across Product, Architecture, Engineering, and Data Science to deliver intelligent systems that solve complex business problems, while optimizing data pipelines and deploying models reliably at cloud scale.

Responsibilities

• Deliver ML models and software components to address challenging needs in the financial services industry in partnership with Product, Architecture, Engineering, and Data Science teams
• Drive the creation and ongoing evolution of ML models and software for state-of-the-art intelligent systems
• Lead large-scale ML initiatives with a customer-first mindset
• Use cloud-based architectures and technologies to deliver optimized ML models at scale
• Optimize data pipelines that feed ML models
• Apply programming languages such as Python, Scala, or Java to build and enhance systems
• Promote best practices across engineering and modeling lifecycles
• Recruit, nurture, and retain top engineering talent
• Act as a force-multiplier for the team by balancing deep, hands-on contributions and innovation with mentoring and raising the skills of peers and junior engineers
• Stay current on technology trends through experimentation, learning new tools and techniques, participating in internal and external technology communities, and mentoring others

Requirements

• Bachelor's Degree or higher in Computer Science, Machine Learning, or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
• At least 3 years of people leadership experience
• At least 8 years of experience programming with Python, Java, Golang, or C++
• At least 6 years of Machine Learning experience using industry standard frameworks PyTorch or TensorFlow and libraries (Pandas, NumPy, Scikit-learn)
• At least 6 years operating large-scale distributed systems (Spark, Ray) to prepare AI or Machine Learning data
• At least 5 years deploying and operating production Machine Learning solutions and production services in the cloud (AWS, GCP, Azure) and using Kubernetes for large-scale containerized ML systems

Technologies

• Python, Scala, Java, Golang, C++
• PyTorch, Tensorflow, Pandas, NumPy, Scikit-learn
• Spark, Ray
• AWS, GCP, Azure, Kubernetes
• Open source frameworks, distributed systems, cloud-based architectures

Benefits

• 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

Preferred Qualifications

• Master's or Doctoral Degree in Computer Science, Electrical Engineering, Mathematics, or related field
• 5+ years of experience managing and leading an engineering team
• 3+ years of experience architecting and designing resilient, large-scale, production machine learning systems from data preparation through model training and inference
• 5+ years of experience optimizing ML algorithms, configurations, and infrastructure
• 5+ years working with Machine Learning techniques (Supervised, semi-supervised, and unsupervised, reinforcement learning, etc.) across model types (Regression, Classification, Clustering, etc.) and model architectures (RNNs, CNNs, LSTMs, Transformers), including training concepts (loss function, hyperparameters, regularization) and evaluating accuracy and diagnosing issues such as underfitting and overfitting
• 7+ years designing, implementing, and scaling production-ready data pipelines for training and evaluating ML models
• Ability to communicate complex technical concepts to a variety of audiences
• Driving impacts through conference presentations, papers, blog posts, open source contributions, or patents
• Experience hiring and developing high-performing ML engineers with an inspiring leadership style
• Highly developed interpersonal, presentation, and communications skills

Location: McLean, VA (onsite)

Compensation: $269,100 - $307,200 per year for Director, Machine Learning Engineer