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Science Engineer Jobs in Milwaukee, WI (NOW HIRING)

Techvilla Solutions

ML Ops Engineer

Saint Francis, WI · On-site

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot production ML systems and optimize reliability, scalability, and performance. * Implement security ...

New

Techvilla Solutions

ML Ops Engineer

Thiensville, WI · On-site

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot production ML systems and optimize reliability, scalability, and performance. * Implement security ...

New

Techvilla Solutions

ML Ops Engineer

North Lake, WI · On-site

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot production ML systems and optimize reliability, scalability, and performance. * Implement security ...

New

Techvilla Solutions

ML Ops Engineer

Milwaukee, WI · On-site

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot production ML systems and optimize reliability, scalability, and performance. * Implement security ...

New

Techvilla Solutions

ML Ops Engineer

Waukesha, WI · On-site

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot production ML systems and optimize reliability, scalability, and performance. * Implement security ...

New

Techvilla Solutions

ML Ops Engineer

Nashotah, WI · On-site

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot production ML systems and optimize reliability, scalability, and performance. * Implement security ...

New

Techvilla Solutions

ML Ops Engineer

River Hills, WI · On-site

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot production ML systems and optimize reliability, scalability, and performance. * Implement security ...

New

Techvilla Solutions

ML Ops Engineer

Fox Point, WI · On-site

Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams. * Troubleshoot production ML systems and optimize reliability, scalability, and performance. * Implement security ...

New

Directsupply

AI Engineer

Milwaukee, WI

Degree in Computer Science, Engineering, Data Science, or a related field * Experience operating AI systems in production, with attention to evaluation, cost, and performance tradeoffs * Background ...

Varsity Tutors

Physical Science Tutor

Milwaukee, WI · Remote

$18 - $40/hr

Emphasizes building scientific inquiry skills and conceptual understanding, connecting physical science to technology, engineering applications, and everyday phenomena. * Curriculum Awareness ...

Varsity Tutors

Data Science Tutor

Milwaukee, WI · Remote

$18 - $40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery: Deep knowledge of statistical ... programming, hypothesis testing, and communication of data-driven insights. Ability to explain ...

Direct Supply, Inc.

AI Engineer

Milwaukee, WI · On-site

$90 - $120/hr

Degree in Computer Science, Engineering, Data Science, or a related field * Experience operating AI systems in production, with attention to evaluation, cost, and performance tradeoffs * Background ...

Direct Supply, Inc.

AI Engineer

Milwaukee, WI · On-site

Degree in Computer Science, Engineering, Data Science, or a related field * Experience operating AI systems in production, with attention to evaluation, cost, and performance tradeoffs * Background ...

Continuus Technologies LLC

Staff Data Engineer

Germantown, WI · On-site

$116K - $139K/yr

... Science, Engineering, or related field (or equivalent experience)7+ years of experience in data engineering or related rolesAdvanced SQL and strong proficiency in Python (or similar language)Deep ...

ATI

Data Scientist

Cudahy, WI · On-site

B.S. degree in computer science, engineering with a strong statistical and programming background. * Experience in deep learning, predictive modeling, data mining, and time series analysis.

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Showing results 41-60

All JobsScience Engineer JobsScience Engineer Jobs in Milwaukee, WI

Science Engineer information

What is a science engineer?

Science engineers are professionals who apply scientific principles and methods to solve technical problems and develop new technologies. They often work at the intersection of research and application, using their expertise in fields such as physics, chemistry, biology, or materials science to design innovative products, improve existing processes, and conduct experiments. Science engineers collaborate with researchers, engineers, and other specialists to translate scientific discoveries into practical solutions for industries like healthcare, energy, manufacturing, and environmental management.

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

To thrive as a Science Engineer, you need a strong background in engineering principles, scientific analysis, and problem-solving, typically supported by a relevant engineering degree. Familiarity with technical tools such as CAD software, simulation programs, and data analysis platforms, as well as certifications like Professional Engineer (PE), are often required. Strong communication, teamwork, and critical thinking skills help distinguish top performers in this field. These competencies ensure innovative solutions, effective project execution, and collaboration across interdisciplinary teams.

What are some common challenges science engineers face when working on interdisciplinary teams?

Science Engineers often collaborate with professionals from diverse backgrounds, such as chemists, physicists, and computer scientists. One common challenge is bridging communication gaps due to different terminologies and approaches used in each discipline. Successfully navigating these differences requires strong interpersonal skills and a willingness to learn from team members. Adapting to varying project management styles and aligning on shared goals are also key aspects of effective interdisciplinary teamwork.

What is the difference between Science Engineer vs Mechanical Engineer?

AspectScience EngineerMechanical Engineer
Required CredentialsBachelor's or higher in science or engineering fields, certifications varyBachelor's or higher in mechanical engineering, PE license optional
Work EnvironmentResearch labs, development centers, industrial settingsManufacturing plants, design offices, testing facilities
Employer & Industry UsageResearch institutions, tech companies, government agenciesManufacturing firms, automotive, aerospace, energy sectors
Common Search & ComparisonYesYes

Science Engineers focus on applying scientific principles to develop new technologies and conduct research, often working in labs or research centers. Mechanical Engineers design, analyze, and manufacture mechanical systems, working primarily in industrial and manufacturing environments. While both roles require engineering knowledge, Science Engineers emphasize scientific research, whereas Mechanical Engineers focus on practical system design and production.

What are popular job titles related to Science Engineer jobs in Milwaukee, WI?

For Science Engineer jobs in Milwaukee, WI, the most frequently searched job titles are:

What job categories do people searching Science Engineer jobs in Milwaukee, WI look for?

The top searched job categories for Science Engineer jobs in Milwaukee, WI are:

What cities near Milwaukee, WI are hiring for Science Engineer jobs?

Cities near Milwaukee, WI with the most Science Engineer job openings:

Science Engineer jobs near you
Infographic showing various Science Engineer job openings in Milwaukee, WI as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 20% Part Time, and 4% Contract. Highlights an 78% Physical, 4% Hybrid, and 18% Remote job distribution.

ML Ops Engineer

Techvilla Solutions

Saint Francis, WI • On-site

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

We are looking for an experienced ML Ops Engineer to build, automate, and maintain scalable machine learning infrastructure and deployment pipelines. The ideal candidate will have strong experience with cloud platforms, CI/CD, containerization, model deployment, monitoring, and ML lifecycle management.

Roles and Responsibilities
  • Build and maintain MLOps pipelines for model development, deployment, monitoring, and retraining.
  • Automate ML workflows using CI/CD, infrastructure as code, and workflow orchestration.
  • Deploy and manage machine learning models across cloud and on-premise environments.
  • Implement model versioning, experiment tracking, feature management, and model governance.
  • Build scalable infrastructure using Docker, Kubernetes, and cloud services.
  • Monitor model performance, data quality, system health, and production workloads.
  • Collaborate with Data Scientists, ML Engineers, Data Engineers, and DevOps teams.
  • Troubleshoot production ML systems and optimize reliability, scalability, and performance.
  • Implement security, access controls, logging, and compliance best practices.
Required Skills
  • 5+ years of experience in DevOps, ML Engineering, MLOps, or a related field.
  • Strong experience with MLOps concepts and ML lifecycle management.
  • Hands-on experience with Python and scripting.
  • Experience with AWS, Azure, or GCP.
  • Strong knowledge of Docker and Kubernetes.
  • Experience with CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or Azure DevOps.
  • Experience with MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML, or similar ML platforms.
  • Experience with Git, Terraform, and infrastructure automation.
  • Knowledge of model monitoring, observability, data validation, and model performance tracking.
  • Strong understanding of REST APIs, microservices, Linux, and cloud-native architectures.
Preferred Skills
  • Experience with Apache Airflow, Databricks, Spark, or Kafka.
  • Knowledge of LLMOps/GenAI deployment and monitoring.
  • Experience with model serving frameworks such as KServe, Seldon, or NVIDIA Triton.
  • Familiarity with Prometheus, Grafana, ELK, or similar observability tools.
  • Understanding of ML security, governance, and responsible AI practices.
Education

Bachelor’s degree in Computer Science, Engineering, Data Science, or a related technical field, or equivalent practical experience.

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