Overview We're seeking a Machine Learning Engineer to help design, build, and maintain production ... Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow ...
Overview We're seeking a Machine Learning Engineer to help design, build, and maintain production ... Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow ...
Overview We're seeking a Machine Learning Engineer to help design, build, and maintain production ... Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow ...
Overview We're seeking a Machine Learning Engineer to help design, build, and maintain production ... Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow ...
As a Machine Learning Engineer II - 3D Perception, you'll join a collaborative team of machine learning engineers and researchers focused on solving complex real-world perception challenges. This ...
As a Machine Learning Engineer II - 3D Perception, you'll join a collaborative team of machine learning engineers and researchers focused on solving complex real-world perception challenges. This ...
Machine Learning Engineer
Dearborn, MI · On-site
Stefanini is looking for a Machine Learning Engineer(Dearborn, MI) For quick apply, please reach out to Navneet Pathak at / We are looking for candidates who will be responsible for predicting and ...
Machine Learning Engineer
Dearborn, MI · On-site
Stefanini is looking for a Machine Learning Engineer(Dearborn, MI) For quick apply, please reach out to Navneet Pathak at / We are looking for candidates who will be responsible for predicting and ...
They are seeking a Staff Machine Learning Engineer to set the technical direction for autonomous refining operations, focusing on building, validating, and optimizing control models across their ...
They are seeking a Staff Machine Learning Engineer to set the technical direction for autonomous refining operations, focusing on building, validating, and optimizing control models across their ...
Staff Machine Learning Engineer
Ann Arbor, MI · On-site
$160K - $240K/yr
As a Staff Machine Learning Engineer at Mariana, you'll set the technical direction for how we make refining autonomous. You'll define how control models are built, validated, and trusted on live ...
Staff Machine Learning Engineer
Ann Arbor, MI · On-site
$160K - $240K/yr
As a Staff Machine Learning Engineer at Mariana, you'll set the technical direction for how we make refining autonomous. You'll define how control models are built, validated, and trusted on live ...
Machine Learning Engineer, II - 3D Perception
Ann Arbor, MI · On-site
$150 - $200/hr
Support and mentor Machine Learning Engineer I team members on implementation, experimentation, and machine learning best practices. Document technical work, evaluation results, and design decisions ...
Machine Learning Engineer, II - 3D Perception
Ann Arbor, MI · On-site
$150 - $200/hr
Support and mentor Machine Learning Engineer I team members on implementation, experimentation, and machine learning best practices. Document technical work, evaluation results, and design decisions ...
We're seeking a highly motivated AI / Machine Learning Engineer who thrives at the intersection of ... Exposure to MLOps tools (MLflow, BentoML, SageMaker, Airflow, etc.). * Contributions to open-source ...
We're seeking a highly motivated AI / Machine Learning Engineer who thrives at the intersection of ... Exposure to MLOps tools (MLflow, BentoML, SageMaker, Airflow, etc.). * Contributions to open-source ...
We're seeking a highly motivated AI / Machine Learning Engineer who thrives at the intersection of ... Exposure to MLOps tools (MLflow, BentoML, SageMaker, Airflow, etc.). * Contributions to open-source ...
We're seeking a highly motivated AI / Machine Learning Engineer who thrives at the intersection of ... Exposure to MLOps tools (MLflow, BentoML, SageMaker, Airflow, etc.). * Contributions to open-source ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...
* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...
Machine Learning Engineer
Lansing, MI · On-site
* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...
Machine Learning Engineer
Lansing, MI · On-site
* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...
* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...
* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...
* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...
* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...
Mlops Machine Learning Engineer information
What does an MLOps machine learning engineer do?
An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.
What are the key skills and qualifications needed to thrive as an MLOps machine learning engineer?
To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.
How does an MLOps machine learning engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?
An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.
What is the difference between Mlops Machine Learning Engineer vs Data Scientist?
| Aspect | Mlops Machine Learning Engineer | Data Scientist |
|---|---|---|
| Required Credentials | Bachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps tools | Bachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning |
| Work Environment | Focus on deploying, maintaining, and scaling ML models in production environments | Focus on data analysis, model development, and insights generation |
| Employer & Industry Usage | Tech companies, startups, enterprises implementing ML solutions | Research institutions, analytics firms, tech companies for data insights |
While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.
Are MLOps machine learning engineers in demand?
MLOps machine learning engineers are in high demand due to the increasing adoption of AI and machine learning across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.
Do MLOps Machine Learning Engineers need a degree?
MLOps Machine Learning Engineers typically do not require a formal degree but often have a background in computer science, data science, or related fields. Practical skills in machine learning, cloud platforms, and tools like Docker, Kubernetes, and CI/CD pipelines are highly valued. Certifications and hands-on experience can also enhance job prospects.
What are popular job titles related to Mlops Machine Learning Engineer jobs in Michigan?
For Mlops Machine Learning Engineer jobs in Michigan, the most frequently searched job titles are:
- Flexible Remote Machine Learning Engineer
- Machine Learning Engineer Intern
- Embedded Machine Learning Engineer
- Senior Machine Learning Researcher
- Senior Machine Learning Engineer
- Intuitive Machines
- Google Cloud Machine Learning Engineer
- Junior Machine Learning Engineer
- Learning Developer
- Entry Level Machine Learning Engineer
What job categories do people searching Mlops Machine Learning Engineer jobs in Michigan look for?
The top searched job categories for Mlops Machine Learning Engineer jobs in Michigan are:
What cities in Michigan are hiring for Mlops Machine Learning Engineer jobs?
Cities in Michigan with the most Mlops Machine Learning Engineer job openings:
Machine Learning Engineering
Birmingham, MI
Publicis Groupe Holdings B.V •
Advertising and Public Relations Services • 10K+ employees10,000+ employees
Full-time
Medical, Dental, Vision, Retirement, PTO
Re-posted 16 days ago
Key responsibilities
Design, build, and maintain scalable ML pipelines using cloud services.
Develop and integrate microservices, REST APIs, and webhooks for ML model serving.
Build and maintain ML infrastructure, implement model monitoring, and manage model lifecycle.
Publicis Groupe rating
6.1
Based on 5 frontline employees who took The Breakroom Quiz
38th of 53 rated marketing agency
Job description
Company Description
Hi there! We're Razorfish. We've been leading the marketing industry with our digital expertise since the start of the internet. But in 2020, we did a full reboot. What's different? It all starts with people. Weird, wonderful, complex people - with diverse backgrounds in strategy, creative and technology. But no matter how different we are, we all have one thing in common. We believe our differences are our strength. So we push for inclusion, challenge convention and bring in new perspectives, to inspire new ideas. Because when we connect by understanding what makes people different, we can create unforgettable experiences that enrich lives. Join us at razorfish.com.
OverviewWe're seeking a Machine Learning Engineer to help design, build, and maintain production-grade ML systems across cloud platforms. This role blends software engineering and ML expertise to translate prototypes into scalable solutions. You'll own the full ML lifecycle from development and deployment to monitoring and optimization using tools like Databricks, Vertex AI, and other cloud-native platforms. Strong technical skills, collaboration, and a passion for delivering AI at scale are essential.
For this role, we expect the candidate to demonstrate a track record of: 1. Collaborating with Data Science teams to deploy ML solutions into production. 2. Hands-on MLOps experience, including model deployment, monitoring, and lifecycle management. 3. Designing data warehouses and orchestrating data pipelines to support scalable ML operations.
ResponsibilitiesML System Development & Deployment
- Design, build, and maintain scalable ML pipelines using cloud services (e.g., Vertex AI, Databricks, SageMaker, Azure ML)
- Develop and integrate microservices, REST APIs, and webhooks for ML model serving
- Implement CI/CD pipelines for automated model training, testing, and deployment
- Create robust data processing workflows for model training and inference
MLOps & Infrastructure
- Build and maintain ML infrastructure using modern MLOps practices and tools (e.g., MLflow, Kubeflow, Vertex AI Pipelines)
- Implement model monitoring, versioning, and performance tracking systems
- Design automated retraining pipelines and manage model lifecycle
- Ensure reliability, scalability, and security of models in production
- Optimize inference performance and cost efficiency across cloud platforms
Software Engineering Excellence
- Write clean, maintainable, and well-documented code following best practices
- Implement comprehensive testing strategies including unit, integration, and model testing
- Contribute to technical design reviews and architecture decisions
- Maintain high code quality standards and participate in code reviews
Cross-Functional Collaboration
- Partner with data scientists to productionize research models and prototypes
- Collaborate with data engineers to design efficient data pipelines and feature stores
- Work with product teams to integrate ML capabilities into customer-facing applications
- Participate in agile development processes and cross-functional project planning
- Provide technical guidance and mentorship to junior team members
Education & Experience
- Bachelor's degree in Computer Science, Software Engineering, Data Science, Mathematics, or related field
- 3-4 years of professional experience in ML engineering, software engineering, or data science
- 2+ years of hands-on experience deploying and maintaining ML models in production
- Experience working in collaborative, cross-functional team environments
Technical Skills
- Programming Languages: Strong proficiency in Python and SQL (2+ years)
- ML Frameworks: Experience with XGBoost, TensorFlow, PyTorch, sklearn, or Keras
- Cloud Platforms: Solid hands-on experience with GCP, AWS, or Azure
- ML Platforms: Practical knowledge of Vertex AI, SageMaker, Azure ML, or Databricks
- Analytics & Feature Engineering: Proficient with BigQuery, Redshift, Azure Synapse
- Distributed Processing: Skilled in Databricks, Apache Spark, Dataflow, Pub/Sub, Kafka
- Workflow Orchestration: Experience with Airflow, Cloud Composer, Jenkins
- Networking & Security: Understanding of cloud networking, security, and cost optimization
- MLOps & DevOps: Familiarity with CI/CD, ML lifecycle management
- API Development: Experience with REST APIs and microservices
- Version Control: Proficiency with Git and collaborative development workflows
Core Competencies
- Strong understanding of ML algorithms, model evaluation, and validation
- Experience with data preprocessing, feature engineering, and performance tuning
- Solid software engineering fundamentals and coding best practices
- Awareness of data privacy, security, and ethical AI principles
- Excellent collaboration skills with technical and non-technical stakeholders
- Self-driven learner with curiosity about emerging ML technologies
Preferred Qualifications
Advanced Technical Skills
- MLOps Tools: MLflow, Kubeflow, Vertex AI Pipelines
- Containerization: Docker; basic Kubernetes knowledge
- Specialized ML: Exposure to NLP, computer vision, or deep learning
- Modern ML: Familiarity with LLMs, RAG patterns, transformer architectures
Professional Experience
- Agile development and cross-functional collaboration
- Code review and technical documentation practices
- Interest in mentorship and knowledge sharing
- Experience with model validation and software testing principles
The Power of One starts with our people! To do powerful things, we offer powerful resources. Our best-in-class wellness and benefits offerings include:
- Paid Family Care for parents and caregivers for 12 weeks or more
- Monetary assistance and support for Adoption, Surrogacy and Fertility
- Monetary assistance and support for pet adoption
- Employee Assistance Programs and Health/Wellness/Comfort reimbursements to help you invest in your future and work/life balance
- Tuition Assistance
- Paid time off that includes Flexible Time off Vacation, Annual Sick Days, Volunteer Days, Holiday and Identity days, and more
- Matching Gifts programs
- Flexible working arrangements
- 'Work Your World' Program encouraging employees to work from anywhere Publicis Groupe has an office for up to 6 weeks a year (based upon eligibility)
- Business Resource Groups that support multiple affinities and alliances
The benefits offerings listed are available to eligible U.S. Based employees, are reviewed on an annual basis, and are governed by the terms of the applicable plan documents.
Razorfish is an Equal Opportunity Employer. Our employment decisions are made without regard to actual or perceived race, color, ethnicity, religion, creed, sex, sexual orientation, gender, gender identity, gender expression, pregnancy, childbirth and related medical conditions, national origin, ancestry, citizenship status, age, disability, medical condition as defined by applicable state law, genetic information, marital status, military service and veteran status, or any other characteristic protected by applicable federal, state or local laws and ordinances.
If you require accommodation or assistance with the application or onboarding process specifically, please contact USMSTACompliance@publicis.com.
All your information will be kept confidential according to EEO guidelines.
Compensation Range: $87,210 to $119,300. This is the pay range the Company believes it will pay for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan through a third-party benefits administration system once certain criteria have been met. Temporary roles may also qualify for participation in our 401(k) plan after eligibility criteria have been met. For regular roles, the Company will offer medical coverage, dental, vision, disability, 401k, and paid time off. The Company anticipates the application deadline for this job posting will be 9/1/25.
Compensation Range: USD $87,210.00 - USD $119,300.00/Annually. This is the pay range the Company believes it will pay for this position at the time of this posting. Consistent with applicable law, compensation will be determined based on the skills, qualifications, and experience of the applicant along with the requirements of the position, and the Company reserves the right to modify this pay range at any time. Temporary roles may be eligible to participate in our freelancer/temporary employee medical plan through a third-party benefits administration system once certain criteria have been met. For regular roles, the Company will offer medical coverage, dental, vision, disability, 401k, and paid time off. The Company anticipates the application deadline for this job posting will be 11/15/2025.Employment Type: OTHERWhat Publicis Groupe employees say
Pay
Benefits
Hours and flexibility
Workplace
Get the full story on Breakroom
About Publicis Groupe
Sourced by ZipRecruiter
Industry
Advertising and public relations services and public relations agencies
Company size
10,000+ Employees
Headquarters location
Paris, IDF, FR