
Senior Software Platform Engineer, MLOps - Cambridge. MA
Cambridge, MA · FlexibleFull-time$170–220K/yrSeen todaySeen in employer's feed today
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At a glance
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Job overview
A fast-growing life sciences technology company is seeking a Senior Software Platform Engineer, MLOps to build and scale infrastructure for enterprise AI and machine learning solutions. The role focuses on designing, deploying, and operating production-grade AI services for external customers in regulated environments, including model serving, agent workflows, RAG, observability, and AI lifecycle management. The engineer will own critical platform components and support AI systems used at scale.
Skills & qualifications
Skills
Qualifications
Benefits
Full job description
$170000 - $220000
Job Description A fast-growing technology company in the life sciences space is seeking a Senior Software Platform Engineer, MLOps to help build and scale the infrastructure powering enterprise AI and machine learning solutions. This role sits at the intersection of cloud platform engineering, distributed systems, and modern AI operations.
You will work closely with AI engineers, data teams, and platform engineers to design, deploy, and operate production-grade AI services used by external customers in highly regulated environments. This is a hands-on engineering position focused on building reliable, scalable, secure systems that support model serving, agent workflows, retrieval-augmented generation (RAG), observability, and AI lifecycle management.
The ideal candidate has a track record of owning critical platform components in production and has experience operating AI systems that support real-world users at scale. Required Skills & Experience
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7+ years of software engineering and infrastructure engineering experience
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Strong background building distributed, cloud-native systems in production environments
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Production experience with AI/ML infrastructure, model deployment, and lifecycle management
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Hands-on experience deploying and operating LLM-based applications in production
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Experience with RAG architectures, embeddings, model versioning, and tool/function calling
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Strong Python and TypeScript development skills
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Experience designing and building REST APIs and OpenAPI-based services
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Experience with AWS cloud services and containerized workloads
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Familiarity with Infrastructure as Code tools such as CloudFormation or AWS CDK
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Experience implementing CI/CD pipelines and deployment automation
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Experience with observability, monitoring, logging, alerting, and distributed tracing
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Experience supporting multi-tenant platforms and handling sensitive data
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Strong communication skills and ability to contribute to technical direction
Desired Skills & Experience
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Experience with Databricks MLflow
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Experience with model registries, versioning, and model serving platforms
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Experience building AI evaluation frameworks and quality monitoring systems
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Knowledge of AI security practices including prompt injection protection and tool abuse prevention
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Experience supporting regulated environments requiring auditability and reproducibility
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Experience mentoring engineers and leading technical design reviews
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Experience evaluating AI frameworks, model providers, and serving technologies
What You Will Be Doing Daily Responsibilities
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100% Hands On
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Design, build, and operate AI platform services and APIs
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Own model and prompt lifecycle management across production environments
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Develop infrastructure supporting model serving, inference, and agent-based systems
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Implement RAG capabilities and AI-powered workflows
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Build evaluation, testing, and quality assurance tooling for AI systems
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Establish monitoring, alerting, logging, and observability standards
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Partner with security teams to implement AI and platform security controls
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Build scalable, multi-tenant cloud services supporting enterprise customers
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Develop Infrastructure as Code and deployment automation solutions
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Participate in architecture reviews and technical design discussions
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Create documentation and mentor engineers across the organization
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Support production reliability, performance optimization, and incident response
The Offer
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Competitive base salary of $170,000 - $220,000
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Equity opportunity
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Flexible work arrangements
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Unlimited PTO
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401(k)
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Company-paid life and disability insurance
You will receive the following benefits
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Medical Insurance
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Dental Benefits
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Vision Benefits
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Paid Time Off (PTO)
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401(k)
Applicants must be currently authorized to work in the US on a full-time basis now and in the future. Sponsorship is not available for this position.
Motion Recruitment Partners (MRP) is an Equal Opportunity Employer. All applicants must be currently authorized to work on a full-time basis in the country for which they are applying, and no sponsorship is currently available. Employment is subject to the successful completion of a pre-employment screening. Accommodation will be provided in all parts of the hiring process as required under MRP’s Employment Accommodation policy. Applicants need to make their needs known in advance.
How this job compares
Set against the 9,008 open Software Engineering jobs on Olive Jobs, counted November 14, 2026.
- Pay
- This posting$170–220K/yr
- Massachusetts median$146–235K/yr217 salary ranges
- US median$146–252K/yr7,041 salary ranges
This range's midpoint, $195K, is close to the Massachusetts median midpoint ($193K) — in the middle half of Software Engineering salary ranges in Massachusetts.
- Openings
- Olive Jobs lists 267 open Software Engineering jobs in Massachusetts and 9,008 across the US. 9% of them nationwide are listed as remote or flexible.
- Hiring the most in Massachusetts
- Oracle20 open
- State Street15 open
- Amazon10 open
- Experience
- This posting asks for at least 7 years of experience; Software Engineering postings that state a minimum ask for 7 years at the median (6,876 postings).
- Education
- 2,134 of the 9,008 open Software Engineering jobs (24%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 14, 2026. Figures based on too few postings are left out.
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