Principal Machine Learning Engineer

Lifelancer

. Engage with business leaders and teams to understand workflows, challenges, and goals .

Posted 10/11/2026full-timeRemote • United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in Machine Learning Engineering with a strong focus on AI application design, full-stack development, and cloud platform utilization. Proven ability to lead cross-functional teams, establish engineering standards, and deliver scalable AI solutions from proof of concept to enterprise adoption.

Highest-signal resume keywords

Machine Learning EngineeringPython ProficiencyCloud Platforms (AWS)DevOps (Terraform, CI/CD)Technical Leadership

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningFull-Stack DevelopmentAPI DevelopmentData IntegrationGenerative AIAutomated TestingVersion ControlModular DesignAI Development ToolsEnterprise Architecture

Soft Skills

Clear CommunicationMentorshipCollaboration

Tools & Technologies

TerraformCI/CDCloud-Native ServicesData PipelinesAPIs

Industry Keywords

AI InitiativesTechnical DirectionEvaluation ApproachesUser ExperienceSecurity Compliance

Tech Stack

Tools & technologies

AWSCloudPythonTerraform

About the role

Key responsibilities & impact

Engage with business leaders and teams to understand workflows, challenges, and goals
Identify AI opportunities and define successful solution outcomes
Lead cross-functional teams in converting ambiguous opportunities into well-scoped AI initiatives
Set priorities, technical approaches, success measures, and paths from proof of concept to enterprise adoption
Architect and build AI proofs of concept using LLMs, agentic workflows, retrieval-augmented generation, data pipelines, APIs, cloud-native services, and enterprise platforms
Own consequential technical work hands-on
Evaluate feasibility and business value through practical experimentation
Address data readiness, integration, user experience, security, compliance, performance, cost, and operational needs
Define scalable architectures and create reusable components, documentation, decision records, and handoff materials
Provide technical direction for product and platform teams developing successful proofs of concept into enterprise solutions
Establish engineering standards through technical leadership and mentorship
Guide design decisions, strengthen delivery practices, and help teams navigate uncertainty

Requirements

What you’ll need

Doctorate degree and 2 years of Machine Learning Engineer experience; or Master's degree and 6 years of Machine Learning Engineer experience; or Bachelor's degree and 8 years of Machine Learning Engineer experience; or Associate's degree and 10 years of Machine Learning Engineer experience; or High school diploma / GED and 12 years of Machine Learning Engineer experience
Substantial experience in machine learning and software engineering, including senior technical ownership of applications that progressed beyond a prototype or pilot
Deep full-stack development skills
Python proficiency
Experience developing APIs, application back ends, user interfaces, and data integrations
Experience with modern software design practices
Hands-on 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
Experience with enterprise architecture and integration patterns
Knowledge of access controls, secure handling of sensitive data, reliability, performance, and maintainability
Experience establishing evaluation approaches for AI applications using quantitative and qualitative evidence
Strong software engineering discipline, including automated testing, version control, modular design, code review, documentation, and AI development tools
Demonstrated technical leadership through architecture 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 directing resource allocation
Clear written and verbal communication skills
Experience presenting technical options and trade-offs to technical and business audiences

Benefits

Comp & perks

A comprehensive employee benefits package, including 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 possible
Career development opportunities
Work/life balance support
Financial plans with opportunities to save towards retirement or other goals