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Machine Learning Infrastructure Jobs (NOW HIRING)

LotusLynx

Senior Machine Learning Engineer

Pittsburgh, PA

$97K - $134K/yr

This role will focus on designing, deploying, optimizing, and supporting scalable machine learning infrastructure, feature pipelines, and MLOps workflows that power advanced analytics and AI ...

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Machine Learning Infrastructure information

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$15

$28

$52

How much do machine learning infrastructure jobs pay per hour?

As of Jun 14, 2026, the average hourly pay for machine learning infrastructure in the United States is $28.01, according to ZipRecruiter salary data. Most workers in this role earn between $21.88 and $30.29 per hour, depending on experience, location, and employer.

What is the difference between Machine Learning Infrastructure vs Data Engineer?

AspectMachine Learning InfrastructureData Engineer
Required CredentialsBachelor's in CS, experience with ML toolsBachelor's in CS, experience with data pipelines
Work EnvironmentFocus on ML systems, cloud platformsData pipelines, database management
Employer & Industry UsageTech companies, AI startupsAny industry with data needs, tech firms
Search & Comparison IntentUnderstanding ML system setupBuilding data pipelines

Machine Learning Infrastructure specialists focus on deploying and maintaining systems that support machine learning models, often working with cloud platforms and ML tools. Data Engineers build and manage data pipelines and databases, supporting data collection and processing. While both roles require technical skills and overlap in data handling, Machine Learning Infrastructure is more centered on ML system deployment, whereas Data Engineers focus on data architecture and pipelines.

What are the typical challenges faced by professionals working in Machine Learning Infrastructure roles?

Professionals in Machine Learning Infrastructure often encounter challenges related to scaling systems to handle large datasets, ensuring model reproducibility, and maintaining efficient workflows for both development and deployment. Collaborating closely with data scientists, software engineers, and DevOps teams is crucial to address issues like version control, resource allocation, and performance optimization. Staying updated on evolving tools and cloud platforms is also essential, as the landscape changes rapidly and impacts system design and integration.

What are the key skills and qualifications needed to thrive in Machine Learning Infrastructure, and why are they important?

To excel in Machine Learning Infrastructure, you need a solid background in computer science, software engineering, and distributed systems, often supported by experience in deploying and scaling machine learning models. Familiarity with cloud platforms (like AWS, GCP, or Azure), containerization tools (such as Docker and Kubernetes), and ML workflow systems (e.g., TensorFlow Extended, MLflow) is crucial. Strong problem-solving skills, collaboration, and the ability to communicate technical concepts effectively help you stand out in this field. These skills ensure scalable, reliable, and efficient deployment of ML solutions, enabling organizations to leverage machine learning at production scale.

What is machine learning infrastructure?

Machine learning infrastructure refers to the combination of hardware, software, platforms, and tools necessary to support the development, training, deployment, and maintenance of machine learning models at scale. This includes computing resources like GPUs and CPUs, data storage systems, workflow orchestration tools, model serving frameworks, and monitoring solutions. The goal of ML infrastructure is to streamline and automate the machine learning lifecycle, enabling data scientists and engineers to build and deploy models more efficiently and reliably.
More about Machine Learning Infrastructure jobs
What states have the most Machine Learning Infrastructure jobs? States with the most job openings for Machine Learning Infrastructure jobs include:
What job categories do people searching Machine Learning Infrastructure jobs look for? The top searched job categories for Machine Learning Infrastructure jobs are:
Machine Learning Infrastructure jobs near you
Senior Machine Learning Infrastructure Engineer

Senior Machine Learning Infrastructure Engineer

Unity Technologies

Bellevue, WA • On-site

$122K - $166K/yr

Full-time

Medical, Life, Retirement, PTO

Posted 6 days ago

Job description

The opportunity
Unity is looking for a Senior Machine Learning Infrastructure Engineer to join our Vector Ads team, where we build the real-time systems that power Unity's global advertising platform. This is a high-scale, low-latency environment - processing billions of requests daily to deliver fast, relevant ads to players around the world.
You'll build and operate the infrastructure that brings ML models from training into production, ensuring our ranking, bidding, and targeting systems run reliably at scale. This is a great opportunity for an engineer who's excited to work at the intersection of ML systems and distributed infrastructure, collaborate across teams, and have direct impact on how machine learning shapes the player and advertiser experience.
What you'll be doing
  • Design, build, and maintain the infrastructure that serves ML models in real-time across Unity's ads ecosystem
  • Build and operate scalable model serving pipelines - owning latency, throughput, and reliability in a high-QPS production environment
  • Partner with ML engineers to productionize models, manage model deployments, and improve iteration speed
  • Improve observability, performance, and cost-efficiency of ML serving infrastructure
  • Contribute to architectural decisions around feature serving, model versioning, and inference optimization

What we're looking for
  • Experience building and operating ML infrastructure or model serving systems in production
  • Proficiency in Golang or Python, with strong systems engineering fundamentals
  • Hands-on experience with Kubernetes and container orchestration at scale
  • Familiarity with ML serving frameworks such as Ray Serve, Triton, TorchServe, or similar
  • Understanding of distributed systems, API design, and system reliability
  • Strong collaboration and communication skills in a remote-first environment

You might also have
  • Experience with feature stores, feature pipelines, or online/offline feature serving
  • Background in ad tech, real-time bidding, or programmatic advertising systems
  • Familiarity with infrastructure-as-code such as Terraform
  • Experience with observability tooling - Prometheus, Grafana, OpenTelemetry
  • Background with real-time data pipelines, caching layers, or low-latency serving systems

Additional information
  • Relocation support is not available for this position

Benefits
At Unity, we want our team members to thrive. We offer a wide range of benefits designed to support well-being and work-life balance.
Please note: Benefits eligibility, specific offerings, and coverage vary based on the country and employment status.
While specific benefits vary, here are some of the ways we strive to take care of our eligible team members globally: Comprehensive health, life, and disability insurance | Commute subsidy | Employee stock ownership | Competitive retirement/pension plans | Generous vacation and personal days | Support for new parents through leave and family-care programs | Office food snacks | Mental Health and Wellbeing programs and support | Employee Resource Groups | Global Employee Assistance Program | Training and development programs | Volunteering and donation matching program
Life at Unity
Unity [NYSE: U] is the world's leading game engine, powering play for more than 3 billion consumers each month. The top mobile games in the world, the most played PC indie titles, the most innovative console games, and virtually all of the top XR and Web Games are developed, deployed, and grown in Unity. Unity also enables teams across industries like automotive, manufacturing, and healthcare to design, simulate, and collaborate in 3D - closing the gap between ideas and reality. For more information, please visit www.unity.com.
Unity is a proud equal opportunity employer. We are committed to fostering an inclusive, innovative environment and celebrate our employees across age, race, color, ancestry, national origin, religion, disability, sex, gender identity or expression, sexual orientation, or any other protected status in accordance with applicable law. Our differences are strengths that enable us to support the growing and evolving needs of our customers, partners, and collaborators. If you have a disability that means there are preparations or accommodations we can make to help ensure you have a comfortable and positive interview experience, please fill out this form to let us know.
This position requires the incumbent to have a sufficient knowledge of English to have professional verbal and written exchanges in this language since the performance of the duties related to this position requires frequent and regular communication with colleagues and partners located worldwide and whose common language is English.
Headhunters and recruitment agencies may not submit resumes/CVs through this website or directly to managers. Unity does not accept unsolicited headhunter and agency resumes. Unity will not pay fees to any third-party agency or company that does not have a signed agreement with Unity.
Your privacy is important to us. Please take a moment to review our Prospect Privacy Policy and Applicant Privacy Policy. Should you have any concerns about your privacy, please contact us at DPO@unity.com.
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*Note: This range reflects the anticipated base salary for this position. Beyond base salary, this role may be eligible for equity awards and participation in our company incentive plans (such as annual discretionary bonuses or sales commissions). The final offer amount will depend on several factors, including geographic location and the candidate's relevant experience, professional background, and skill set.
Gross pay salary
$183,700-$248,600 USD

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