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Remote Observability Engineer Jobs in Michigan (NOW HIRING)

Integra Partners

EDI Engineer

Troy, MI · On-site +1

$110K - $110K/yr

... Events, Observability). • Experience with containerization technologies like Docker and ... Career development opportunities Remote Opportunities We are actively seeking new colleagues in:

Gordon Food Service

Senior Software Engineer

Wyoming, MI · On-site +1

$111K - $146K/yr

Hybrid Schedule, 4 days in office in Wyoming, MI or Atlanta, GA, with 1 day remote What you'll ... Observability with Dynatrace and Google Cloud Monitoring * Experience building AI-powered features ...

FastTek

DevOps Specialist

Dearborn, MI · On-site +1

$48.50 - $66.50/hr

Engineer for 99.99% Reliability: Bring a true SRE mindset to our platform. You will design self ... Remote Position - SE Michigan only Additional Info: At FastTek Global, Our Purpose is Our People ...

Abaxis

HPC Platform Product Lead

Portage, MI · On-site +1

Operations, reliability, and observability (20%) * Drive operational excellence via monitoring ... Bachelor's degree in computer science, Engineering, Information Systems, or equivalent practical ...

Hitachi

Vice President of Information Technology

Holland, MI · On-site +1

$149K - $187K/yr

... Remote: No The Opportunity: JR Automation, a Hitachi Group Company, is driven to deliver customer ... A collaborative, engineering-driven environment * Career growth and skill development opportunities

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Remote Observability Engineer information

What is a remote observability engineer?

A Remote Observability Engineer is a professional responsible for designing, implementing, and maintaining systems that monitor the health, performance, and reliability of software applications and infrastructure from a remote location. They use observability tools to collect and analyze logs, metrics, and traces, helping organizations quickly detect and resolve issues. Their work ensures that distributed systems are transparent, reliable, and efficient, often collaborating with development, operations, and security teams. Remote Observability Engineers often work from anywhere, leveraging cloud-based tools and platforms to manage complex IT environments.

What are the typical collaboration patterns for a remote observability engineer working with distributed teams?

Remote Observability Engineers frequently collaborate with software developers, DevOps teams, and IT operations to ensure systems are monitored effectively and issues are detected early. Working remotely, you'll often use communication tools like Slack, Jira, and video conferencing to coordinate incident response, discuss monitoring strategies, and review system health dashboards. Regular sync meetings and asynchronous updates are common, and you'll likely contribute to documentation and knowledge sharing to keep all stakeholders informed. Building strong communication habits is important, as much of the troubleshooting and improvement work hinges on clear coordination with multiple teams.

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

To thrive as a Remote Observability Engineer, you need strong expertise in monitoring, logging, and tracing systems, along with a background in computer science or related technical fields. Familiarity with tools like Prometheus, Grafana, ELK Stack, Datadog, and cloud platforms is typically required, as well as relevant certifications such as AWS Certified Cloud Practitioner or Google Cloud Professional DevOps Engineer. Excellent problem-solving abilities, communication skills, and a proactive mindset help you detect and resolve issues before they impact users. These competencies ensure system reliability, enable rapid incident response, and support seamless collaboration in distributed environments.

What is the difference between Remote Observability Engineer vs Site Reliability Engineer?

AspectRemote Observability EngineerSite Reliability Engineer
CredentialsKnowledge of monitoring tools, scripting, cloud platformsSame as Observability Engineer, plus SRE certifications often preferred
Work EnvironmentFocus on monitoring, logging, and tracing systems remotelyBroader scope including system reliability, incident response, and automation
Industry UsagePrimarily in tech, SaaS, cloud servicesWidely in tech, finance, and large-scale online services

The Remote Observability Engineer specializes in monitoring and analyzing system performance remotely, focusing on tools like logs and metrics. In contrast, the Site Reliability Engineer has a broader role, ensuring overall system reliability, automation, and incident management. While both roles require similar technical skills, SREs often have additional responsibilities related to system resilience and scalability.

What are popular job titles related to Remote Observability Engineer jobs in Michigan?

For Remote Observability Engineer jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Remote Observability Engineer jobs in Michigan look for?

The top searched job categories for Remote Observability Engineer jobs in Michigan are:

What cities in Michigan are hiring for Remote Observability Engineer jobs?

Cities in Michigan with the most Remote Observability Engineer job openings:

Remote Observability Engineer jobs near you

AI Machine Learning Engineer (AI / ML: Python / Go)

Detroit, MI • On-site, Remote

Benzinga
Video and Audio Streaming Services • 11 - 50 employees
Learn more about Benzingaexternal

Full-time

Re-posted 22 days ago

Job description

About Benzinga
Benzinga is a fast-growing financial media and data technology company reshaping how investors access information. We combine artificial intelligence, machine learning, and real-time data pipelines to surface insights before they hit the mainstream. Our platforms deliver structured news, sentiment analytics, and financial data APIs used by leading banks, fintechs, and AI companies worldwide.
We're seeking a highly motivated AI / Machine Learning Engineer who thrives at the intersection of data science and backend engineering - someone who can take a model from notebook to production, and architect intelligent systems in Go and Python that scale to millions of requests.
The ideal candidate is a self-starter who independently identifies opportunities, experiments with new approaches, and ships production-ready solutions without constant direction.
Key Responsibilities
AI / Machine Learning
  • Research, design, and deploy machine learning models across NLP, time-series forecasting, and event detection domains.
  • Build LLM-driven systems (e.g. summarization, RAG pipelines, embedding search) optimized for financial news and quantitative data.
  • Develop model serving APIs and scalable inference layers using Go or Python.
  • Implement model monitoring, drift detection, and continuous retraining pipelines.
  • Work with financial text (earnings call transcripts, filings, news) to extract structured insights.
  • Collaborate with data engineers to build training datasets, feature stores, and embedding databases.

Backend & Infrastructure
  • Develop and maintain high-performance Python or Go microservices that integrate with AI systems and Go data APIs.
  • Design and optimize real-time inference pipelines on AWS, leveraging ECS/EKS, S3, and Lambda.
  • Ensure low-latency, fault-tolerant, and scalable delivery of AI-powered data.
  • Implement CI/CD for ML workflows, including containerization, automated deployment, and versioning.
  • Partner with DevOps to manage cloud infrastructure and ensure robust observability for AI workloads.

Requirement for applying:
  • During your screening you will be required to submit a Loom video walkthrough of your most exceptional product, share relevant code/repo links, and describe the biggest challenge you faced building it.

Required Qualification
  • 4+ years of experience in AI/ML or data engineering roles, with a proven track record of deploying ML models in production.
  • Computer science degree (Bachelor minimum)
  • Deep proficiency in Python (data, ML) and Go (backend, microservices).
  • Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or Hugging Face.
  • Experience with transformer architectures, embeddings, or fine-tuning LLMs.
  • Strong understanding of data pipelines, feature extraction, and model lifecycle management.
  • Familiarity with Docker, Kubernetes, and AWS (EKS, S3, Lambda, EC2).
  • Excellent problem-solving skills and ability to work independently in a distributed environment.

Preferred Skills / Experience
  • Startup experience.
  • Financial services or fintech background
  • Experience building LLM-powered APIs or retrieval-augmented generation (RAG) systems.
  • Knowledge of vector databases (e.g., Pinecone, Weaviate, FAISS, OpenSearch kNN).
  • Experience with Kafka, LangChain, or data streaming architectures.
  • Familiarity with financial data systems, real-time analytics, or news NLP.
  • Exposure to MLOps tools (MLflow, BentoML, SageMaker, Airflow, etc.).
  • Contributions to open-source ML or Go projects are a strong plus.

Tech Stack
  • Languages: Python, Go
  • ML Frameworks: PyTorch, TensorFlow, Hugging Face, LangChain
  • Cloud: AWS (EKS, ECS, S3, Lambda, EC2, IAM)
  • Containers & Orchestration: Docker, Kubernetes
  • Data & Streaming: Kafka, Postgres, OpenSearch
  • CI/CD: GitHub Actions, GitLab CI
  • Monitoring: Datadog, Prometheus, Grafana
  • Version Control: Git (Gitlab / Github)

Why Join Benzinga
  • Build and ship production AI systems that shape how financial markets understand information.
  • Operate with full creative freedom - explore, experiment, and execute your ideas end-to-end.
  • Work with a lean, highly technical team where initiative and ownership are celebrated.
  • Fully remote, high-trust environment that rewards curiosity, speed, and execution.
Benzinga logo

About Benzinga

Sourced by ZipRecruiter

Benzinga is a full-service news and media company with three main areas of expertise: real-time news, actionable trading ideas and insightful commentary. We offer coverage of all aspects of the financial market including corporate, economic and political content. With strong connections in and around the market, we strive to provide high quality and relevant news for the real-time environment that defines today's world.

Industry

Video and audio streaming services

Company size

11 - 50 Employees

Headquarters location

Detroit, MI, US

Year founded

2010

Social media

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