Principal Machine Learning Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Collaborate directly with business leaders and teams to gain insights into workflows, challenges, and objectives.

• Discover AI opportunities and articulate successful solution outcomes.

• Lead cross-functional teams in transforming vague opportunities into well-defined AI initiatives.

• Make decisions regarding priorities, technical strategies, success metrics, and the progression 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 tasks in a hands-on manner.

• Assess feasibility and business value through practical experimentation.

• Address data readiness, integration, user experience, security, compliance, performance, costs, and operational requirements.

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

• Offer technical leadership and mentorship to team members.

• Direct design decisions, enhance delivery practices, and assist teams in navigating uncertainty with clear ownership and accountability.

⛳️ Requirements

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

• Extensive experience in machine learning and software engineering, including senior technical ownership of applications that have advanced beyond a prototype or pilot stage.

• In-depth full-stack development capabilities, encompassing proficiency in Python and experience in developing APIs, application back ends, user interfaces, data integration, and modern software design methodologies.

• Practical experience with cloud platforms, such as AWS, and DevOps practices including Terraform or similar infrastructure as code, containers, CI/CD, automated deployment, and observability.

• Strong practical understanding of generative AI and machine learning application design, covering model selection, evaluation, inference, and trade-offs among managed services, open-source tools, and custom implementations.

• Familiarity with enterprise architecture and integration patterns, addressing access controls, secure management of sensitive data, reliability, performance, and maintainability.

• Experience in establishing evaluation methods for AI applications using both quantitative and qualitative evidence to assess solution quality, user experience, safety, latency, and costs.

• Strong software engineering principles, including automated testing, version control, modular design, code reviews, documentation, and effective utilization of AI development tools.

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

• A minimum of 2 years of experience in directly leading teams, projects, or programs, or managing resource allocation.

• Excellent written and verbal communication skills, with experience presenting technical options and trade-offs to both technical and business audiences.

🏝️ Benefits

• Comprehensive employee benefits package, which includes a Retirement and Savings Plan with generous company contributions.

• Group medical, dental, and vision insurance coverage.

• Life and disability insurance options.

• Flexible spending accounts.

• Discretionary annual bonus program.

• Stock-based long-term incentives.

• Award-winning vacation and time-off plans.

• Flexible work models where applicable.

• Opportunities for career development.

• Financial plans that allow savings towards retirement or other objectives.

• Emphasis on work/life balance.