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Mlops Data Engineer Jobs in Rochester, MI (NOW HIRING)

Programmers.io

Senior Databricks Architect

Detroit, MI · On-site

$64 - $84.25/hr

Contribute to building MLOps and advanced operations frameworks. Required Qualifications * 14+ years in Data Engineering/Architecture with at least 4+ years hands-on Databricks experience delivering ...

Maddisoft

AI Specialist

Rochester, MI · On-site

Strong knowledge of SQL, NoSQL databases, and data engineering concepts. Experience working with ... Experience with MLOps, CI/CD pipelines, and AI model lifecycle management. Familiarity with change ...

Autodesk

Senior Machine Learning Test Engineer

Novi, MI · On-site +1

$103K - $134K/yr

You are a quality-focused developer who is passionate about reliable, repeatable evaluation of ML models and data. Your skills span test strategy, automation, and a little MLOps, with a strong ...

Canopy

Senior Machine Learning Engineer

Detroit, MI · On-site +1

$126K - $180K/yr

Collaborate with cross-functional stakeholders including product managers, data engineers, and MLOps teams to ensure seamless model integration and delivery. * Perform advanced exploratory data ...

Canopy

Senior Machine Learning Engineer

Detroit, MI · Remote

$126K - $180K/yr

Collaborate with cross-functional stakeholders including product managers, data engineers, and MLOps teams to ensure seamless model integration and delivery. * Perform advanced exploratory data ...

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Mlops Data Engineer information

See Rochester, MI salary details

$41K

$119.4K

$163.4K

How much do mlops data engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for mlops data engineer in Rochester, MI is $119,398.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,400.00 and $126,600.00 per year, depending on experience, location, and employer.

What is an MLOps data engineer?

MLOps Data Engineers are professionals who blend expertise in machine learning (ML), operations (Ops), and data engineering to streamline the deployment and management of ML models in production environments. They design and maintain data pipelines, automate workflows, and ensure the scalability, reliability, and reproducibility of machine learning systems. Their role bridges the gap between data scientists and IT operations, enabling seamless integration of ML models into real-world applications.

What are the key skills and qualifications needed to thrive as an MLOps data engineer?

To thrive as an MLOps Data Engineer, you need a strong background in data engineering, machine learning workflows, and software development, usually supported by a degree in computer science or a related field. Expertise with cloud platforms (such as AWS, GCP, or Azure), CI/CD pipelines, containerization tools (like Docker and Kubernetes), and familiarity with orchestration frameworks are typically required, along with certifications in cloud or data engineering. Strong problem-solving abilities, collaboration, and clear communication set professionals apart in this role. These skills and qualities are critical to efficiently deploying scalable machine learning solutions and ensuring smooth collaboration between data science and engineering teams.

What are some common challenges MLOps data engineers face when deploying machine learning models into production?

MLOps Data Engineers often encounter challenges such as ensuring seamless integration between data pipelines and model serving infrastructure, managing consistent data quality, and automating model retraining and monitoring. Another common hurdle is maintaining scalability and reliability as data volumes grow, and efficiently collaborating with data scientists, software engineers, and DevOps teams. Addressing these challenges requires strong communication skills, familiarity with cloud platforms, and a proactive approach to troubleshooting and automation.

What is the difference between Mlops Data Engineer vs Data Scientist?

AspectMlops Data EngineerData Scientist
Required SkillsMachine learning deployment, cloud platforms, scripting, data pipelinesStatistical analysis, programming, data visualization, machine learning modeling
CertificationsCloud certifications, ML engineering coursesData science certifications, statistical courses
Work EnvironmentData pipelines, cloud infrastructure, ML deployment systemsData analysis, modeling, research environments
Industry UsageTech companies, AI-focused firms, cloud service providersResearch institutions, analytics firms, tech companies

The main difference between an Mlops Data Engineer and a Data Scientist lies in their focus areas. Mlops Data Engineers specialize in deploying, maintaining, and scaling machine learning models within production environments, emphasizing infrastructure and automation. Data Scientists primarily focus on analyzing data, building models, and deriving insights. Both roles require strong technical skills, but their day-to-day tasks and career paths differ significantly.

Are MLOps Data Engineers in demand?

MLOps Data Engineers are in high demand due to the increasing adoption of machine learning and AI across industries. They are skilled in deploying, managing, and maintaining ML models using tools like Docker, Kubernetes, and cloud platforms, making their expertise highly sought after in data-driven organizations.

Is MLOps required for data engineers?

MLOps is increasingly important for data engineers involved in deploying and maintaining machine learning models, as it encompasses practices like automation, monitoring, and version control. While not always mandatory, knowledge of MLOps tools such as Docker, Kubernetes, and CI/CD pipelines enhances a data engineer's ability to support scalable and reliable ML systems.

What job categories do people searching Mlops Data Engineer jobs in Rochester, MI look for?

The top searched job categories for Mlops Data Engineer jobs in Rochester, MI are:

What cities near Rochester, MI are hiring for Mlops Data Engineer jobs?

Cities near Rochester, MI with the most Mlops Data Engineer job openings:

Mlops Data Engineer jobs near you
Infographic showing various Mlops Data Engineer job openings in Rochester, MI as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 14% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $119,398 per year, or $57.4 per hour.

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

Benzinga

Detroit, MI • Remote

Full-time

Re-posted yesterday

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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