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Remote Machine Learning Compiler Engineer Jobs in Detroit, MI

Data Scientist

Warren, MI · On-site +1

Lead the execution of assigned AI, machine learning, or data science workstreams from methodology ... Partner cross-functionally with data engineering, software delivery, product delivery teams ...

Application Engineer

Detroit, MI · On-site +1

$85K - $130K/yr

Remote in Michigan, preferably near Detroit On-Target Compensation: $85,000 - $130,000 ... Skilled in machine commissioning and creating application/machine specifications * Familiarity with ...

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Deep knowledge of statistical analysis, data wrangling, exploratory data analysis, machine learning, data visualization, SQL, Python or R programming, hypothesis testing, and communication of data ...

Showing results 41-60

Remote Machine Learning Compiler Engineer information

See Detroit, MI salary details

$74.2K

$165.8K

$202.9K

How much do remote machine learning compiler engineer jobs pay per year?

As of Sep 11, 2026, the average yearly pay for remote machine learning compiler engineer in Detroit, MI is $165,757.00, according to ZipRecruiter salary data. Most workers in this role earn between $141,600.00 and $202,900.00 per year, depending on experience, location, and employer.

What is a remote machine learning compiler engineer?

A Remote Machine Learning Compiler Engineer is a software engineer who specializes in developing and optimizing compilers specifically for machine learning workloads, while working from a remote location. Their primary responsibilities include designing and implementing compiler features that translate machine learning models into efficient code for various hardware platforms, such as CPUs, GPUs, or specialized accelerators. They collaborate closely with machine learning researchers, hardware engineers, and software developers to ensure high performance and compatibility. In addition to strong programming skills, they typically require expertise in compiler theory, machine learning frameworks, and hardware architectures. This role allows for flexible, location-independent work while contributing to cutting-edge AI technologies.

How does a remote machine learning compiler engineer typically collaborate with cross-functional teams to optimize model deployment?

As a Remote Machine Learning Compiler Engineer, you will frequently collaborate with data scientists, hardware engineers, and software developers to ensure that machine learning models are efficiently compiled and deployed on target platforms. Communication often takes place through virtual meetings, code reviews, and shared documentation tools. You'll be responsible for translating research models into optimized code, troubleshooting performance bottlenecks, and integrating feedback from various stakeholders. Effective teamwork is crucial, as the success of deployments often depends on iterative feedback and close alignment with both the ML research and hardware teams.

What are the key skills and qualifications needed to thrive as a remote machine learning compiler engineer, and why are they important?

To thrive as a Remote Machine Learning Compiler Engineer, you need a strong background in computer science, proficiency in programming languages like C++ and Python, and expertise in compiler theory and machine learning frameworks. Familiarity with ML compilers such as TVM or XLA, and experience using version control and CI/CD systems are commonly required, along with a relevant bachelor's or master's degree. Outstanding problem-solving, collaboration, and communication skills are essential for working effectively in distributed teams and across technical domains. These skills and qualities enable the development of efficient, scalable ML solutions that bridge software and hardware, ensuring high performance and innovation.

What is the difference between Remote Machine Learning Compiler Engineer vs Remote Data Scientist?

AspectRemote Machine Learning Compiler EngineerRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Software Engineering, or related fields; knowledge of compiler design and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in programming, statistics, and data analysis
Work EnvironmentPrimarily software development, compiler optimization, and ML model deploymentData analysis, model building, and interpretation of results
Industry UsageTech companies, AI startups, hardware firms focusing on ML hardware accelerationTech, finance, healthcare, and research organizations

While both roles involve working with machine learning, the Remote Machine Learning Compiler Engineer focuses on developing and optimizing compilers for ML models, whereas the Remote Data Scientist concentrates on analyzing data and building predictive models. The roles share some technical skills but differ in their core responsibilities and work environments.

What are popular job titles related to Remote Machine Learning Compiler Engineer jobs in Detroit, MI?

For Remote Machine Learning Compiler Engineer jobs in Detroit, MI, the most frequently searched job titles are:

What job categories do people searching Remote Machine Learning Compiler Engineer jobs in Detroit, MI look for?

The top searched job categories for Remote Machine Learning Compiler Engineer jobs in Detroit, MI are:

Staff Site Reliability Engineer

Ann Arbor, MI • On-site, Remote

Sight Machine, Inc.
Software Development • 11 - 50 employees

$55.75 - $74/hr

Full-time

Medical, Life, PTO

Posted 23 days ago


Job description

Team Culture
Great things happen when people can bring their authentic selves to work. We empower all of our employees to share their perspectives, passions and experiences because collectively we make a better, stronger team. Our team members collaborate closely with peers & cross functional stakeholders throughout the business, our clients on the forefront of digital transformation, and the cutting edge of digital manufacturing thought leadership.
We take pride in our self-starter culture where employees are enabled and encouraged to achieve their professional goals through leadership guidance, learning and development. Our philosophy is that careers are continuous journeys, and we dedicate time and offer resources so that employees can reach their full potential.
Benefits + Perks
We value you at and outside of work and know your loved ones are important. Our benefits are designed to support you and your family's health through life's expected and unexpected events.
Our Benefits Include:
  • Competitive Salary + Stock Options
  • Health Care Coverage + Life Insurance + Health Savings Account + Flexible Spending
  • Account (includes spouse + children)
  • Flexible Vacation Policy
  • Adaptable Working Schedule and Environment
  • Our Perks Include:
  • Casual Dress Attire
  • Hybrid work flexibility
  • Catered Lunches, Snacks and Beverages
  • Commuter Savings Program
  • Company Outings
  • Designated Volunteering Hours + Group Volunteer Events

Sight Machine is proud to be an equal opportunity employer and considers candidates regardless of age, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Sight Machine also considers qualified applicants regardless of criminal histories, consistent with legal requirements.
About Sight Machine, Inc.
Sight Machine strengthens manufacturers by providing the industry's only standard data model and system-level visualization capabilities. By integrating all crucial data into a single innovative platform, everyone involved in the fabrication process can visualize, contextualize and examine data in one intuitive interface.
Sight Machine is committed and mission-driven to improve lives, strengthen communities and make the world cleaner through continuously re-envisioning manufacturing processes - making them more efficient, sustainable and absolute.
Founded in Michigan in 2011 and expanded to San Francisco in 2012, Sight Machine blends the spirit of technology innovation and the down to earth style of Detroit manufacturing. Our team includes early leadership from Yahoo, Tesla Motors and Oracle. Together, we share wide industry knowledge and a commitment to advance manufacturing to a more sustainable future.
We take pride in our self-starter culture where employees are enabled and encouraged to achieve their professional goals through leadership guidance, learning and development. Our philosophy is that careers are continuous journeys, and we dedicate time and offer resources so that employees can reach their full potential.
Sight Machine is proud to be an equal opportunity employer and considers candidates legally authorized to work in the US regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Sight Machine also considers qualified applicants regardless of criminal histories, consistent with legal requirements.
About the team
Sight Machine is built on the shoulders of a unique, robust and highly scalable Infrastructure as Code model. This enables the creation and operation of customer instances in our ecosystem in a standardized and simplified manner. We are looking for team members to help us build, maintain, and improve the infrastructure that makes Sight Machine the leading provider of Manufacturing Data Pipelines and Analytics.
Great things happen when people can bring their authentic selves to work. We empower all of our team members to share their perspectives, passions and experiences because collectively we make a better, stronger team through always "open communications" mind.
Our team collaborates closely with peers & cross functional stakeholders throughout the business, our clients on the forefront of digital transformation, and the cutting edge of digital manufacturing thought leadership.
Sight Machine has offices in San Francisco, CA and Ann Arbor, Mi. We do have a remote-friendly culture with people based all around the US and the rest of the world. For this role in particular, the ideal candidate is located near either of our offices and willing to work in a hybrid capacity. We would still consider 100% remote for exceptional candidates if they aren't located near an office.
About the role
Join the Cloud Infrastructure Team as a technical leader driving reliability, automation, and scalability across the systems running Sight Machine's platform. You'll operate at the intersection of classic SRE discipline which include IaC, CI/CD, observability, incident response and the emerging demands of running agentic AI systems in production: LLM gateways, agent orchestration, and the operational patterns that come with non-deterministic workloads.
This is a senior level IC role. You'll help set and drive technical direction for infrastructure and reliability practices across teams, mentor senior engineers, and be a primary escalation point for the org's hardest systems problems while still being hands-on with code, infrastructure, and incidents.
Success requires deep technical range, sound judgment on risk vs. customer impact, and the ability to influence architecture decisions across Development Engineering without formal authority.
What You'll Actually Work On
  • Champion an agentic-AI-first engineering mindset: identify where AI-driven automation and agent-based tooling can replace manual toil, and hold that work to the same quality, testing, and reliability bar as any other production system
  • Evolve reliability practices for meeting reliability SLO's, error budgets, drive incident postmortems to systemic (not just symptomatic) fixes, and lead reliability reviews for new services before they hit production
  • Troubleshoot and resolve the org's most complex, cross-layer systems problems CI/CD, container orchestration, networking, OS, cloud resources, databases, and increasingly, agentic AI/LLM orchestration layers
  • Design, build, and operate the infrastructure supporting agentic AI workloads, LLM gateway routing, agent orchestration frameworks, monitoring of non-deterministic/AI-driven services, and the operational tooling needed to run them reliably at scale
  • Architect and instrument monitoring, alerting, and observability infrastructure for critical services, with an eye toward what "critical" means for AI-driven systems specifically
  • Author and continuously improve operational runbooks and automation, increasingly incorporating agentic/AI-assisted tooling (e.g., automated triage, AI-assisted incident response) where it measurably reduces toil
  • Design and build internal platforms and developer tooling that other engineers build on top of
  • Participate in on-call coverage and help evolve the program as we scale including escalation paths and reducing avoidable pages through better automation
  • Bring a startup mindset of daily engagement: staying close to what's breaking, what customers are hitting, and where the team needs help, even outside a formal ticket or rotation
  • Mentor senior and mid-level engineers; act as a technical sounding board across teams
  • Proactively identify and drive cross-team initiatives that improve stability, reliability, and availability, this is expected to be self-directed, not assigned

What We're Looking For
  • Demonstrated experience designing, building, or operating agentic AI/LLM-based systems in production, held to the same quality-first, test-driven rigor as traditional infrastructure code, not just prototype-grade work
  • Embody a quality-first and security-first culture in all that you do
  • 10+ years of experience with Kubernetes/Docker in at least one top-tier cloud provider (Azure, GCP, AWS), including production-scale multi-tenant or multi-cluster environments
  • 10+ years coding experience (Python, Go, Java, or similar) with a track record of building tools/platforms used by other engineers, not just scripts
  • 10+ years with IaC and CI/CD tooling (Terraform/OpenTofu, FluxCD or similar GitOps tooling, Jenkins/GitHub Actions)
  • Strong, provable Linux and networking fundamentals (TCP/IP and application-layer)
  • Practical experience integrating or operating LLM/agentic AI systems in a production context this can be API-based orchestration, LLM gateways, or agent frameworks
  • A track record of authoring technical documentation (design docs, ADRs, runbooks) that other engineers actually use
  • Demonstrated mentorship of other engineers, without needing formal management authority to do it
  • Strong bias for action over endless planning, hands-on, has made mistakes, learned from them, and can weigh risk vs. customer impact under pressure
  • Clear, empathetic communicator, comfortable pushing back on architecture decisions across teams
  • Operational experience with monitoring/alerting systems (Prometheus, Grafana, Loki, Sentry, Signoz or equivalents)
  • Deep understanding of cloud performance, able to diagnose and resolve bottlenecks others can't

Nice to Have
  • Experience with elements of our current tech stack are a plus: Kubernetes, FluxCD, Terraform, Helm Charts, Prometheus, Elasticsearch, Python, Java, Kafka, Postgres, and Jenkins
  • Previous experience or a keen interest in industrial IoT, analytics, or manufacturing a plus