Principal Machine Learning Engineer

This is a fully remote position, open to applicants in District of Columbia, +1 more state.

📋 Description

• Collaborate with business leaders and teams to comprehend workflows, challenges, and objectives.

• Recognize AI opportunities and outline successful solution outcomes.

• Lead cross-functional teams to transform ambiguous opportunities into clearly defined AI initiatives.

• Establish priorities, technical methodologies, success metrics, and pathways from proof of concept to enterprise implementation.

• Design and construct AI proofs of concept utilizing LLMs, agentic workflows, retrieval-augmented generation, data pipelines, APIs, cloud-native services, and enterprise platforms.

• Take ownership of significant technical work hands-on.

• Assess feasibility and business value through practical experimentation.

• Tackle issues related to data readiness, integration, user experience, security, compliance, performance, cost, and operational requirements.

• Define scalable architectures and develop reusable components, documentation, decision records, and handoff materials.

• Offer technical guidance for product and platform teams in transforming successful proofs of concept into enterprise solutions.

• Establish engineering standards through technical leadership and mentoring.

• Steer design choices, enhance delivery practices, and assist teams in managing uncertainty.

⛳️ Requirements

• Doctorate degree with 2 years of experience as a Machine Learning Engineer; or a Master’s degree with 6 years of experience; or a Bachelor’s degree with 8 years of experience; or an Associate’s degree with 10 years; or a High school diploma/GED with 12 years of experience in Machine Learning Engineering.

• Significant experience in machine learning and software engineering, including senior technical ownership of applications that have progressed beyond a prototype or pilot phase.

• Profound full-stack development expertise.

• Proficiency in Python.

• Experience in developing APIs, application back ends, user interfaces, and data integrations.

• Familiarity with modern software design methodologies.

• Practical experience with cloud platforms such as AWS.

• DevOps experience, including Terraform or similar infrastructure as code, containers, CI/CD, automated deployment, and observability.

• Strong practical knowledge of generative AI and machine learning application design.

• Experience with model selection, evaluation, inference, and trade-offs among managed services, open-source tools, and custom implementations.

• Familiarity with enterprise architecture and integration frameworks.

• Understanding of access controls, secure handling of sensitive data, reliability, performance, and maintainability.

• Experience establishing evaluation methodologies for AI applications using both quantitative and qualitative evidence.

• Strong software engineering discipline, including automated testing, version control, modular design, code review, documentation, and AI development tools.

• Proven technical leadership through architectural decisions, mentorship, and collaboration across business, product, engineering, security, and platform teams.

• At least 2 years of experience directly leading teams, projects, or programs, or managing resource allocation.

• Excellent written and verbal communication skills.

• Experience presenting technical options and trade-offs to both technical and business audiences.

🏝️ Benefits

• A comprehensive employee benefits package, featuring a Retirement and Savings Plan with generous company contributions.

• Group medical, dental, and vision coverage.

• Life and disability insurance.

• Flexible spending accounts.

• A discretionary annual bonus program.

• Stock-based long-term incentives.

• Award-winning time-off plans.

• Flexible work models where feasible.

• Opportunities for career development.

• Support for work/life balance.

• Financial plans with options to save for retirement or other goals.