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Ml Platform Engineer Jobs (NOW HIRING)

Interon IT Solutions

MLOps Platform Engineer

Reston, VA · On-site

This role will play a key part in enabling scalable, reliable, and secure ML model development and deployment across our cloud and container platforms. This is a hands-on engineering role requiring ...

Apply Early

Interon IT Solutions

MLOps Platform Engineer

Reston, VA · On-site

This role will play a key part in enabling scalable, reliable, and secure ML model development and deployment across our cloud and container platforms. This is a hands-on engineering role requiring ...

Apply Early

Whisker Labs

Senior ML Platform Engineer

$107K - $146K/yr

Whisker Labs is seeking a Senior ML Platform Engineer to join our fully remote Data Science team. As part of the team, you will be responsible for advancing Whisker Labs' technology to detect early ...

CSAA

Job Title Software Engineer III - AI/ML Platform Operations - Remote Requisition Number R7739 Software Engineer III - AI/ML Platform Operations - Remote (Open) Location Arizona - Home Teleworkers ...

CSAA

Job Title Software Engineer III - AI/ML Platform Operations - Remote Requisition Number R7739 Software Engineer III - AI/ML Platform Operations - Remote (Open) Location Arizona - Home Teleworkers ...

CSAA

Job Title Software Engineer III - AI/ML Platform Operations - Remote Requisition Number R7739 Software Engineer III - AI/ML Platform Operations - Remote (Open) Location Arizona - Home Teleworkers ...

CSAA

Job Title Software Engineer III - AI/ML Platform Operations - Remote Requisition Number R7739 Software Engineer III - AI/ML Platform Operations - Remote (Open) Location Arizona - Home Teleworkers ...

CSAA

Job Title Software Engineer III - AI/ML Platform Operations - Remote Requisition Number R7739 Software Engineer III - AI/ML Platform Operations - Remote (Open) Location Arizona - Home Teleworkers ...

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All JobsMl Platform Engineer Jobs

Ml Platform Engineer information

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How much do ml platform engineer jobs pay per hour?

As of Jul 5, 2026, the average hourly pay for ml platform engineer in the United States is $63.95, according to ZipRecruiter salary data. Most workers in this role earn between $50.48 and $73.80 per hour, depending on experience, location, and employer.

What are ML Platform Engineers?

ML Platform Engineers are specialized software engineers who design, build, and maintain the infrastructure and tools needed to support the development, deployment, and scaling of machine learning models. They bridge the gap between data science and production engineering by automating model training, monitoring, versioning, and serving. Their work enables data scientists to focus on modeling while ensuring that ML solutions are reliable, reproducible, and scalable in real-world environments.

What is the difference between Ml Platform Engineer vs Data Scientist?

AspectML Platform EngineerData Scientist
Required credentialsBachelor's/Master's in CS, Engineering, or related; experience with cloud platformsBachelor's/Master's in Statistics, Math, or CS; strong programming skills
Work environmentBuilds and maintains ML infrastructure, collaborates with engineering teamsAnalyzes data, develops models, and interprets results
Industry usageTech companies, AI startups, enterprises deploying ML systemsResearch institutions, tech firms, data-driven organizations

ML Platform Engineers focus on developing and maintaining the infrastructure that supports machine learning models, while Data Scientists primarily analyze data and build models. Both roles often collaborate but serve different functions within the AI and data ecosystem.

How does an ML Platform Engineer typically collaborate with data scientists and software engineers within a company?

ML Platform Engineers work closely with both data scientists and software engineers to streamline the process of developing, deploying, and maintaining machine learning models. They provide the infrastructure and tools necessary for data scientists to build and experiment with models efficiently, while ensuring seamless integration with production systems managed by software engineers. Regular communication, participation in cross-functional meetings, and shared project management tools are common ways teams collaborate. This close collaboration helps to bridge the gap between research and production, ensuring robust, scalable, and reliable ML solutions.

What are the key skills and qualifications needed to thrive as an ML Platform Engineer, and why are they important?

To thrive as an ML Platform Engineer, you need a strong background in computer science, software engineering, and machine learning concepts, often supported by a degree in a related field. Expertise with cloud platforms (such as AWS, GCP, or Azure), containerization (Docker, Kubernetes), CI/CD pipelines, and knowledge of ML frameworks (TensorFlow, PyTorch) are commonly required. Collaboration, problem-solving, and strong communication skills help you work efficiently with data scientists, engineers, and stakeholders. These skills ensure the development, scalability, and reliability of robust ML infrastructure that empowers teams to deploy and manage models effectively.
More about Ml Platform Engineer jobs
What cities are hiring for Ml Platform Engineer jobs? Cities with the most Ml Platform Engineer job openings:
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Ml Platform Engineer jobs near you
Infographic showing various Ml Platform Engineer job openings in the United States as of June 2026, with employment types broken down into 42% Full Time, 53% Part Time, 1% Temporary, and 4% Contract. Highlights an 83% Physical, 4% Hybrid, and 13% Remote job distribution, with an average salary of $133,026 per year, or $64 per hour.
Staff AI/ML Platform Engineer

Staff AI/ML Platform Engineer

Albert Invent

Oakland, CA • On-site

Full-time

Posted 3 days ago

Job description

Albert's mission is to digitalize the world of chemistry. Using data and machine learning, Albert enables R&D organizations to dramatically accelerate the invention of new materials. Our platform helps scientists and engineers build structured data foundations, digitize formulation and testing workflows, and apply AI to innovate faster, smarter, and at scale.
About the role
As our AI/ML Platform Engineer, you will build the foundational systems that enable AI at the bench-the APIs, data pipelines, and workflow orchestration that turn ambitious AI capabilities into tools scientists can actually use.
We're building the lab of the future: a system where AI helps scientists invent faster, discover more, and optimize better. That future depends on a robust platform that can serve models in real-time, orchestrate complex multi-step pipelines, and integrate seamlessly with the data infrastructure that gives AI its understanding of chemistry. You'll be at the center of that work.
This is a foundational role with real influence. Our platform is robust but still in its early days-you'll have the opportunity to shape architecture decisions, introduce new technologies, and build systems that directly enable researchers at the world's largest chemical companies to leverage AI in ways that weren't possible before.
At Albert Invent, we value curiosity, rigor, and openness. We're writing the playbook for AI-augmented science together. If you want to build the infrastructure that makes that possible, we'd love to hear from you.
What you'll do
We are seeking an exceptional AI/ML Platform Engineer to join our AI/ML team. You'll own the APIs, data pipelines, and workflow orchestration that power our AI products-from real-time model inference to long-running optimization pipelines. This role sits at the intersection of backend engineering and data engineering: you'll build the services that serve up models, manage workflows, and connect AI capabilities to the structured data that makes them useful.
You'll work closely with our Active Learning and LLM/Agents team leads, translating their product vision into scalable, production-grade systems. The infrastructure you build will power model playgrounds for chemists, inverse design pipelines that optimize experiments across high-dimensional spaces, and orchestrated agent workflows that reason through complex scientific problems.
API & Backend Development
  • Design and build high-performance Python APIs that serve models, manage workflows, and expose AI capabilities to the broader platform
  • Architect backend services for scalability, reliability, and low latency
  • Build integrations between AI/ML systems, graph databases, and external data sources

Pipeline & Workflow Orchestration
  • Build and maintain long-running workflow pipelines using Ray and Temporal
  • Design orchestration patterns for multi-step agent pipelines, batch inference, and numerical optimization workflows
  • Ensure fault tolerance, graceful degradation, and efficient resource utilization

Data Infrastructure
  • Architect and maintain data pipelines that feed AI/ML workflows
  • Work with Neptune (graph), Redis, DynamoDB, and other data stores to enable efficient data access patterns
  • Build the connectors and transformations that give AI systems access to clean, structured, trusted data

Platform Reliability & Operations
  • Implement observability including logging, metrics, tracing, and alerting
  • Own system reliability-troubleshoot issues, conduct post-mortems, and continuously improve
  • Design CI/CD pipelines and promote automation best practices

Collaboration & Influence
  • Partner with ML researchers, data scientists, and product engineers to understand requirements and deliver production-ready infrastructure
  • Collaborate closely with Active Learning and LLM/Agents team leads to align platform capabilities with product needs
  • Contribute to architectural decisions that shape how AI gets built and shipped at Albert
You will have
  • Deep expertise in Python backend development and building production APIs
  • Experience designing and operating data pipelines and workflow orchestration systems
  • A builder's mindset-you want to create foundational systems that others build on
  • Genuine curiosity about how your work enables scientific discovery
  • A commitment to rigor: AI makes mistakes confidently, and our customers won't accept hand-waving-neither should we

Key competencies
  • A degree in Computer Science or a related field with 7+ years of industry experience (Bachelor's) or 5+ years (Master's or PhD) in software engineering
  • Advanced proficiency in Python including async programming and performance optimization
  • Experience building and maintaining REST APIs using FastAPI or similar frameworks
  • Experience with workflow orchestration tools (Ray, Temporal, or similar)
  • Strong background in data engineering: pipelines, transformations, and working with diverse data stores
  • Experience with cloud platforms (AWS preferred) and containerization (Docker, Kubernetes)
  • Familiarity with graph databases, key-value stores, or other NoSQL systems (Neptune, Redis, DynamoDB a plus)
  • Track record of operating production systems at scale

Preferred/Bonus Points
  • Experience supporting AI/ML teams or deploying ML systems in production
  • Familiarity with distributed computing frameworks (Ray, Dask, Spark)
  • Experience with GPU workloads and scheduling
  • Background in or curiosity about chemistry, materials science, or scientific computing
  • Experience with observability tools (Prometheus, Grafana, Datadog)
  • Experience with message queues and event-driven architectures
  • Contributions to open-source projects
  • Experience mentoring engineers
Why Albert?
We have a huge impact. Albert is a growing team with a big reach. Our Platform facilitates the invention of materials for tens of thousands of companies and hundreds of thousands of applications - from coatings used on rockets to adhesives used in electric vehicles to 3D printed medical devices. We love distributed teams. Albert's home-base is in the California Bay Area, but we have multiple offices and employees sprinkled around the globe. In fact, over 50% of our employees work outside of California! An international remote culture is in our DNA. We care about you. Albert works hard to create a positive environment for our employees, and we think your life outside of work is important too. We work hard and we play hard. We value diversity. Growing and maintaining our inclusive and diverse team matters to us. We are committed to being a company where our employees feel comfortable bringing their authentic selves to work and have the ability to be successful - every day. We're always looking for humble, sharp, and creative folks to join the Albert team. If you think you might be a fit please apply!

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