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Machine Learning Platform Engineer

Job in Manchester, Hillsborough County, New Hampshire, 03101, USA
Listing for: Motion Recruitment
Full Time position
Listed on 2026-10-24
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Cloud Engineer - Software, Machine Learning/ ML Engineer, DevOps
Salary/Wage Range or Industry Benchmark: 195000 - 250000 USD Yearly USD 195000.00 250000.00 YEAR
Job Description & How to Apply Below
Position: Staff Machine Learning Platform Engineer
Manchester, New Hampshire Open to Remote Full Time $195k - $250k

Job Description
A forward-thinking technology organization building advanced AI-powered platforms is seeking a Staff Machine Learning Platform Engineer to join its distributed engineering team. This fully remote opportunity is focused on attracting top talent located in New Hampshire who are passionate about developing the infrastructure that enables machine learning and generative AI solutions to operate reliably s position sits at the intersection of software engineering, cloud architecture, machine learning operations, and distributed computing.

The successful candidate will help define how AI applications are built, deployed, secured, and monitored across a multi-tenant environment while partnering closely with engineering and data teams to support rapidly evolving business needs.
The ideal candidate has extensive experience designing production-grade AI systems, enjoys tackling complex scalability challenges, and can provide technical leadership across large engineering initiatives. You will play a key role in establishing engineering standards, platform capabilities, and architectural best practices that support long-term growth.
Required Skills & Experience 10+ years of experience building and supporting enterprise software platforms Strong expertise in cloud-native architecture and distributed systems design Demonstrated success leading major technical initiatives and architectural decisions Significant experience operating machine learning infrastructure in production environments Hands-on experience supporting LLM-powered applications and AI-driven products Deep understanding of model deployment workflows, governance practices, and lifecycle management

Experience with vector databases, retrieval architectures, embeddings, and RAG solutions Advanced proficiency in Python and Type Script Strong API development experience using modern REST-based architectures Experience building applications and services on AWS Working knowledge of Docker and containerized application deployment Experience implementing Infrastructure as Code solutions using AWS CDK, Cloud Formation, or similar technologies Knowledge of monitoring, observability, incident response, and site reliability practices Experience securing cloud platforms handling sensitive customer information Strong communication and collaboration skills across technical and non-technical stakeholders
Desired Skills & Experience Experience implementing AI agents and autonomous workflow solutions Familiarity with modern model orchestration and prompt management frameworks Knowledge of GPU workload optimization and AI infrastructure cost management

Experience with model evaluation frameworks, testing pipelines, and quality measurement systems Exposure to multimodal AI applications involving image processing and scientific data Familiarity with fine-tuning, model optimization, and performance tuning methodologies Experience working within regulated industries and compliance-focused environments Background supporting scientific, healthcare, biotechnology, or laboratory technology organizations
What You Will Be Doing Daily Responsibilities Develop and enhance the engineering platform that supports machine learning and AI workloads Build scalable infrastructure that enables reliable model serving and inference processing Establish standards for model registration, deployment, promotion, and governance Design platform capabilities to support both streaming and batch AI workloads Create secure architectures that enforce tenant isolation and data protection requirements Build systems that improve AI reliability through testing, validation, and performance monitoring Implement logging, tracing, alerting, and platform observability capabilities Partner with engineering teams to improve scalability, reliability, and operational efficiency Lead architecture discussions and guide technical strategy across multiple projects Mentor engineers and provide subject matter expertise in machine learning infrastructure Research emerging technologies and recommend platform improvements Support CI/CD initiatives and infrastructure automation efforts to accelerate delivery
The Offer Competitive compensation package Fully remote role for candidates located in New Hampshire Opportunity to contribute to enterprise-scale AI and machine learning initiatives Collaborative engineering environment with significant technical ownership…
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