Staff Machine Learning Engineer - Infrastructure

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Staff Machine Learning Engineer - Infrastructure in the United States.

In this role, you will lead the design and development of scalable ML infrastructure that powers end-to-end machine learning workflows. You will collaborate closely with data scientists, product teams, and engineers to define architecture, implement best practices, and optimize ML pipelines from prototyping to deployment and monitoring. Your work will shape the technical roadmap, improve operational efficiency, and ensure high reliability across ML systems. This position offers a flexible, remote-friendly environment with opportunities to influence ML strategy and mentor other engineers. The ideal candidate is proactive, technically expert, and thrives in a fast-paced, collaborative environment where innovation and operational excellence go hand in hand.

Accountabilities:

• Design, implement, and maintain scalable ML infrastructure on AWS, supporting data pipelines, feature stores, model training, deployment, and monitoring.
• Collaborate with ML Science, Product, and Engineering teams to refine technical designs and integrate ML capabilities with core products.
• Drive adoption of best practices in MLOps, operational excellence, governance, and security across the organization.
• Provide mentorship and guidance to Data+ML team members on engineering skills, architecture, and business communication.
• Influence technical direction, roadmap, and architecture decisions for ML infrastructure across multiple teams and projects.
• Ensure high reliability, availability, and SLA adherence for ML systems and services.

Requirements

• 6+ years experience in ML engineering with deep expertise in ML architecture, MLOps, data pipelines, feature stores, and inference/monitoring infrastructure on AWS.
• Experience building large-scale, compliant ML platforms in regulated industries such as financial services.
• Skilled in designing ML infrastructure with product-oriented, user experience-centered approaches.
• Strong communication and interpersonal skills with the ability to influence stakeholders and collaborate across teams.
• Proven ability to structure and execute complex projects while measuring performance and impact.
• BS degree preferred; strategic mindset, proactive, high ethical standards, and bias toward action.

Benefits

• Flexible remote-first work environment with options to work from home or office.
• Competitive salary based on location tier: National ($176,800–$221,000), Premium ($191,400–$239,200), Premium Plus ($208,000–$260,000).
• Annual performance bonuses recognizing individual and company contributions.
• Multiple health insurance options, including medical, dental, and vision coverage.
• Flexible time off policy, retirement savings program with company contributions, and equity opportunities.
• Family-forming benefits, fertility support, and up to 20 weeks parental leave.
• Access to professional development, coaching, and wellness support.
• Monthly stipend to support remote work and home office needs.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

When you apply, your profile goes through our AI-powered screening process designed to identify top talent efficiently and fairly:

• 🔍 Our AI evaluates your CV and LinkedIn profile thoroughly, analyzing your skills, experience, and achievements.
• 📊 It compares your profile to the job’s core requirements and past success factors to determine your match score.
• 🎯 Based on this analysis, we automatically shortlist the 3 candidates with the highest match to the role.
• 🧠 When necessary, our human team may perform an additional manual review to ensure no strong profile is missed.

The process is transparent, skills-based, and free of bias — focusing solely on your fit for the role. Once the shortlist is completed, it is shared directly with the company, who then manages interviews and next steps.

Thank you for your interest!