Remote AI ML Platform Jobs
Remote AI ML Platform jobs are open across the U.S. in sectors like cloud infrastructure, enterprise software, and data-intensive industries, at companies ranging from remote-first AI startups to large distributed engineering teams. Employers hiring remotely right now include ICAAI, reddit, and Peraton. See the openings below and apply to the ones that match your experience.
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We're Blue River, a team of innovators driven to create intelligent machinery that solves monumental problems for our customers. We empower our customers – farmers, construction crews, and foresters - to implement safer and more sustainable solutions, driving increased profitability with less reliance on scarce labor. We believe that focusing on the small stuff – pixel-by-pixel and task-by-task - leads to big gains.
Blue River Technology aligns with John Deere's vision to "innovate on behalf of humanity" by quickly identifying and solving high-value, high-uncertainty challenges in AI, machine learning, computer vision, and robotics. BRT acts as a research and development flywheel, building not only new products but also new platforms that reliably create value for both Deere and its customers. From fully autonomous machines to highly precise farming equipment, BRT and Deere are partnering to create technical breakthroughs in industries like agriculture and construction.
Our people are at the heart of what we do. Through cross-disciplinary collaboration, this mission-driven team is eager to define the new frontier of robotics. We are always asking hard questions, rapidly iterating, and getting our boots in the field to figure it out. We won't give up until we've made a tangible and positive impact on the planet!
Blue River Technology is based in Santa Clara, CA.
Summary
We are looking for a senior software engineer with a strong background in ML infrastructure and platform engineering who is passionate about building the foundational systems that enable machine learning teams to move faster. Rather than developing ML models, this role focuses on designing scalable platforms, developer tooling, and infrastructure that support the full ML lifecycle across cloud and on-premises environments.
- Employment Type: Full-Time
- Work Location: Remote in the United States.
- Visa sponsorship is possible for this position.
Job Responsibilities
A combination, not necessarily all-inclusive, of the following:
- Design, build, and operate scalable ML infrastructure and platform capabilities that support the full machine learning lifecycle across cloud and on-premises environments.
- Develop developer tooling, services, and infrastructure that enable ML and engineering teams to build, deploy, and operate production systems more efficiently.
- Independently lead complex technical initiatives from problem definition and architecture through implementation, production rollout, and ongoing operational ownership.
- Make sound architectural and engineering decisions that balance near-term delivery with the platform's long-term scalability, reliability, and maintainability.
- Build reliable, scalable, easy-to-use platform capabilities that improve developer productivity, simplify operations, and help engineering teams move faster.
- Partner closely with ML engineers, infrastructure engineers, and other stakeholders to understand customer needs and translate them into effective platform solutions.
- Identify and solve challenging infrastructure and platform problems, including opportunities to improve performance, reliability, scalability, and developer experience.
- Drive adoption and continuous improvement of platform capabilities by incorporating feedback from the engineering teams that use them.
- Establish a high bar for software quality, operational excellence, and production readiness across the systems and capabilities you own.
- Deliver platform solutions with measurable engineering and business impact across multiple teams and use cases.
Required Experience and Skills
- 5+ years of professional software engineering experience, with a focus on platform, infrastructure, or distributed systems.
- Strong Python engineering skills, including building production services, SDKs, automation, or platform tooling.
- Experience designing, building, and operating production platform capabilities used by multiple engineering teams.
- Understanding of ML platform architecture and the end-to-end ML lifecycle, including experimentation, distributed training, model deployment, and production operations.
- Experience building and operating applications on Kubernetes and cloud platforms (AWS preferred), with an understanding of production reliability, observability, and operational best practices.
- Strong technical judgment with the ability to independently lead complex technical initiatives from discovery through production, collaborating effectively with ML engineers, infrastructure teams, and product stakeholders.
Preferred Experience and Skills
- Experience building developer platforms, tooling, or internal services that improve engineering productivity and reduce operational complexity.
- Experience with workflow orchestration or distributed compute technologies such as Airflow, Kubeflow, Ray, Spark, or similar systems.
- Experience designing and optimizing distributed, GPU-intensive compute platforms for ML training, inference, or large-scale image processing.
- Experience supporting production machine learning platforms in computer vision, robotics, or similar domains.
- Demonstrated technical leadership through architecture, mentorship, or influencing technical direction across teams.
At Blue River, your base pay is one part of your total compensation package. For this position, the reasonably expected pay range is between $160,000 - $287,000/year for the level at which this job has been scoped. Your base pay will depend on several factors, including your experience, qualifications, education, location, and skills. This position is also eligible for an annual performance bonus and a competitive benefit package. During the recruitment process, we may identify an alternative role or level to which you are more suited. If your ideal role at Blue River differs from the advertised position, we will provide an updated pay range as soon as possible during the hiring process.
We're passionate about creating an inclusive workplace that promotes and values diversity. While we have more work to do to advance diversity and inclusion, we're investing in our programs, including recruiting, mentorship, career development, and learning & development, to ensure they support our Diversity, Equity, and Inclusion goals. We support each employee in living a full life, enabling a thriving career, and accomplishing a meaningful, challenging mission while collaborating with incredible people. We are dedicated to building a diverse and inclusive workplace, so if you're excited about this role but your experience doesn't align completely with the job description, we encourage you to apply anyway.
We are an equal-opportunity employer and do not discriminate based on race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, perform essential job functions, and receive other benefits and privileges of employment. Please contact us to request an accommodation.
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Who's Hiring


Top Industries Hiring
- Technology & Software
- Media & Entertainment
What Employers Look For
The qualifications that appear most often in remote AI ML platform jobs.
- Proficiency in Python and experience building or maintaining ML pipelines at scale
- Hands-on experience with containerization and orchestration tools such as Docker and Kubernetes
- Familiarity with at least one managed ML platform such as SageMaker, Vertex AI, or Azure ML
- Experience designing or operating distributed training and model serving infrastructure
- Understanding of CI/CD principles applied to model training, evaluation, and deployment workflows
- Bachelor's or master's degree in computer science, engineering, or a closely related quantitative field
Tips for Your Remote AI ML Platform Job Search
Show your async collaboration skills upfront
Remote ai ml platform teams run on written communication. Highlight experience with async-first tools like Confluence, Notion, or Slack documentation in your materials. Employers screening for remote readiness look for candidates who can unblock themselves and communicate decisions clearly in writing.
Build a public portfolio of platform work
Remote hiring managers can't watch you work, so a public GitHub with real MLOps pipelines, feature stores, or model serving infrastructure does the work for you. Documented projects that show you've built and maintained shared ML platform components are far more persuasive than a job title alone.
Apply early to remote roles that fit
Migrate Mate lists remote ai ml platform openings from across the U.S. in one place. Search the current openings, find roles that match your stack and seniority, and apply directly. Remote roles often close faster than on-site ones because the candidate pool is national.
Prepare for a remote-native technical interview
Remote ai ml platform interviews typically include live system design sessions over video with shared diagramming tools like Miro or Excalidraw. Practice talking through distributed training infrastructure, model serving architectures, and pipeline observability out loud, since remote interviewers are assessing how clearly you communicate technical decisions.
Remote AI ML Platform Jobs: Frequently Asked Questions
How do I get a remote ai ml platform job?
Remote ai ml platform roles go to candidates who can demonstrate self-directed execution and strong async communication alongside deep technical skills. Remote-first software companies and distributed AI teams are the most consistent hirers. Showing proficiency in MLOps tooling, model deployment pipelines, and infrastructure-as-code gives you a concrete edge, and a portfolio of shipped platform work is far more persuasive than credentials alone when you're competing for a fully remote seat.
Which companies hire remote ai ml platforms?
Companies hiring remote ai ml platforms right now include ICAAI, reddit, and Peraton, based on current remote listings on Migrate Mate as of September 2026. Remote-first technology firms and distributed engineering teams across cloud services, enterprise AI, and data infrastructure are the most consistent sources of these openings.
Can you get a remote ai ml platform job with no experience?
Yes, but remote entry-level ai ml platform roles are harder to land because employers expect you to work independently from day one with minimal hand-holding. Your best path is contributing to open-source MLOps or platform projects, building a public portfolio of pipeline or infrastructure work, and targeting smaller remote-first AI companies that are more willing to invest in developing junior platform engineers.
Do you need a degree for remote ai ml platform jobs?
Not always. Remote employers hiring ai ml platform engineers weigh demonstrated skills, shipped platform projects, and familiarity with tools like Kubernetes, Kubeflow, Ray, or cloud ML services more heavily than a diploma. A strong GitHub history, contributions to ML infrastructure projects, or certifications in cloud and MLOps can substitute effectively, especially at remote-first companies that evaluate candidates primarily on technical output.
Which industries hire the most remote ai ml platforms?
Most remote ai ml platform openings sit in Technology & Software and Media & Entertainment, per current remote listings on Migrate Mate as of September 2026. These sectors rely on distributed engineering teams that build and maintain shared ML infrastructure across multiple product lines and geographies, making remote platform roles structurally natural.
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