Senior Mlops Engineer Jobs
Senior Mlops Engineer jobs are open across technology, finance, healthcare, and retail, from mid-level to staff and principal, with specializations in model deployment, pipeline automation, and ML infrastructure. Find a role that fits from the openings below and apply directly.
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Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications. In addition to your pay, Target cares about and invests in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation. Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits.
About us:
Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here.
About the Role:
As a Senior Engineer, you serve as a specialist in the engineering team that supports the product. You help develop and gain insight in the application architecture. You can distill an abstract architecture into concrete design and influence the implementation. You show expertise in applying the appropriate software engineering patterns to build robust and scalable systems. You are an expert in programming and apply your skills in developing the product. You have the skills to design and implement the architecture on your own, but choose to influence your fellow engineers by proposing software designs, providing feedback on software designs and/or implementation. You show good problem solving skills and can help the team in triaging operational issues. You leverage your expertise in eliminating repeat occurrences.
As a Sr Engineer on the MLOps Platform team, you will help design, build, and evolve an enterprise MLOps platform that enables teams to develop, deploy, and operate machine learning and Generative AI solutions at scale.
You will combine strong software engineering and platform engineering fundamentals with an understanding of ML and AI workflows. You will partner with Data Scientists, ML Engineers, product managers, and platform teams to build secure, reliable, and easy-to-use capabilities across the AI/ML lifecycle.
This is a hands-on engineering role focused on building platforms, services, and developer experiences that enable AI/ML teams to move from experimentation to production.
What You Will Do:
- Design, build, test, and operate scalable services and capabilities for an enterprise MLOps platform.
- Build APIs, microservices, and event-driven systems that support ML and Generative AI workflows.
- Develop platform capabilities for model development, deployment, serving, monitoring, and lifecycle management.
- Enable Generative AI use cases including LLMs, RAG, embeddings, vector search, and agentic applications through reusable platform capabilities.
- Integrate with cloud AI/ML services, data platforms, model providers, and enterprise systems.
- Build automation and self-service experiences that improve developer and Data Scientist productivity.
- Implement observability, evaluation, governance, security, and reliability capabilities across the ML lifecycle.
- Optimize platform services for scalability, availability, performance, and cost.
- Apply strong engineering practices including automated testing, CI/CD, infrastructure automation, and operational excellence.
- Collaborate across engineering, Data Science, product, security, and infrastructure teams and mentor other engineers through design and code reviews.
Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.
About You:
- 5+ years of professional software engineering experience building and operating production systems.
- Strong proficiency in Java or a comparable object-oriented programming language; experience with Python is beneficial.
- Experience with REST APIs, microservices, distributed systems, SQL/NoSQL databases, Docker, Kubernetes, Git, and CI/CD.
- Experience building or supporting platforms, developer tooling, or infrastructure services.
- Understanding of the machine learning lifecycle, including experimentation, training, deployment, serving, monitoring, and model management.
- Familiarity with MLOps practices and technologies for production ML systems.
- Experience with cloud platforms; GCP preferred
- Familiarity with Generative AI technologies including LLMs, RAG, embeddings, vector databases, and AI agents.
- Experience with monitoring, observability, security, and reliability of production systems.
- Ability to independently design and deliver scalable platform capabilities.
- Strong communication and collaboration skills across engineering, Data Science, product, and platform teams.
Desired Qualifications:
- Experience building or operating an enterprise MLOps or AI platform.
- Experience with cloud ML platforms such as Gemini Enterprise Agent Platform (Vertex AI) or equivalent technologies.
- Experience with Kubernetes-based ML infrastructure and model serving.
- Experience enabling Generative AI capabilities through shared platforms or services.
- Experience designing self-service developer platforms, SDKs, APIs, or tooling.
Benefits Eligibility
Please paste this url into your preferred browser to learn about benefits eligibility for this role: https://tgt.biz/BenefitsForYou_DAmericans with Disabilities Act (ADA)
In compliance with state and federal laws, Target will make reasonable accommodations for applicants with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process, please reach out to candidate.accommodations@HRHelp.Target.com. Non-accommodation-related requests, such as application follow-ups or technical issues, will not be addressed through this channel.
Application deadline is : 09/25/2026Pay is based on several factors which vary based on position. These include labor markets and in some instances may include education, work experience and certifications. In addition to your pay, Target cares about and invests in you as a team member, so that you can take care of yourself and your family. Target offers eligible team members and their dependents comprehensive health benefits and programs, which may include medical, vision, dental, life insurance and more, to help you and your family take care of your whole selves. Other benefits for eligible team members include 401(k), employee discount, short term disability, long term disability, paid sick leave, paid national holidays, and paid vacation. Find competitive benefits from financial and education to well-being and beyond at https://corporate.target.com/careers/benefits.
About us:
Working at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here.
About the Role:
As a Senior Engineer, you serve as a specialist in the engineering team that supports the product. You help develop and gain insight in the application architecture. You can distill an abstract architecture into concrete design and influence the implementation. You show expertise in applying the appropriate software engineering patterns to build robust and scalable systems. You are an expert in programming and apply your skills in developing the product. You have the skills to design and implement the architecture on your own, but choose to influence your fellow engineers by proposing software designs, providing feedback on software designs and/or implementation. You show good problem solving skills and can help the team in triaging operational issues. You leverage your expertise in eliminating repeat occurrences.
As a Sr Engineer on the MLOps Platform team, you will help design, build, and evolve an enterprise MLOps platform that enables teams to develop, deploy, and operate machine learning and Generative AI solutions at scale.
You will combine strong software engineering and platform engineering fundamentals with an understanding of ML and AI workflows. You will partner with Data Scientists, ML Engineers, product managers, and platform teams to build secure, reliable, and easy-to-use capabilities across the AI/ML lifecycle.
This is a hands-on engineering role focused on building platforms, services, and developer experiences that enable AI/ML teams to move from experimentation to production.
What You Will Do:
- Design, build, test, and operate scalable services and capabilities for an enterprise MLOps platform.
- Build APIs, microservices, and event-driven systems that support ML and Generative AI workflows.
- Develop platform capabilities for model development, deployment, serving, monitoring, and lifecycle management.
- Enable Generative AI use cases including LLMs, RAG, embeddings, vector search, and agentic applications through reusable platform capabilities.
- Integrate with cloud AI/ML services, data platforms, model providers, and enterprise systems.
- Build automation and self-service experiences that improve developer and Data Scientist productivity.
- Implement observability, evaluation, governance, security, and reliability capabilities across the ML lifecycle.
- Optimize platform services for scalability, availability, performance, and cost.
- Apply strong engineering practices including automated testing, CI/CD, infrastructure automation, and operational excellence.
- Collaborate across engineering, Data Science, product, security, and infrastructure teams and mentor other engineers through design and code reviews.
Core responsibilities of this job are described within this job description. Job duties may change at any time due to business needs.
About You:
- 5+ years of professional software engineering experience building and operating production systems.
- Strong proficiency in Java or a comparable object-oriented programming language; experience with Python is beneficial.
- Experience with REST APIs, microservices, distributed systems, SQL/NoSQL databases, Docker, Kubernetes, Git, and CI/CD.
- Experience building or supporting platforms, developer tooling, or infrastructure services.
- Understanding of the machine learning lifecycle, including experimentation, training, deployment, serving, monitoring, and model management.
- Familiarity with MLOps practices and technologies for production ML systems.
- Experience with cloud platforms; GCP preferred
- Familiarity with Generative AI technologies including LLMs, RAG, embeddings, vector databases, and AI agents.
- Experience with monitoring, observability, security, and reliability of production systems.
- Ability to independently design and deliver scalable platform capabilities.
- Strong communication and collaboration skills across engineering, Data Science, product, and platform teams.
Desired Qualifications:
- Experience building or operating an enterprise MLOps or AI platform.
- Experience with cloud ML platforms such as Gemini Enterprise Agent Platform (Vertex AI) or equivalent technologies.
- Experience with Kubernetes-based ML infrastructure and model serving.
- Experience enabling Generative AI capabilities through shared platforms or services.
- Experience designing self-service developer platforms, SDKs, APIs, or tooling.
Benefits Eligibility
Please paste this url into your preferred browser to learn about benefits eligibility for this role: https://tgt.biz/BenefitsForYou_DAmericans with Disabilities Act (ADA)
In compliance with state and federal laws, Target will make reasonable accommodations for applicants with disabilities. If a reasonable accommodation is needed to participate in the job application or interview process, please reach out to candidate.accommodations@HRHelp.Target.com. Non-accommodation-related requests, such as application follow-ups or technical issues, will not be addressed through this channel.
Application deadline is : 09/25/2026Senior Mlops Engineer Jobs by Experience Level
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Who's Hiring
Top Industries Hiring
- Technology & Software
What Employers Look For
The qualifications that appear most often in senior mlops engineer jobs.
- 3 or more years of experience building and maintaining production ML pipelines
- Proficiency with orchestration tools such as Airflow, Kubeflow, or Prefect
- Hands-on experience with at least one major cloud platform: AWS, GCP, or Azure
- Strong Python skills including packaging, testing, and environment management
- Experience with containerization and Kubernetes for model serving and scaling
- Familiarity with CI/CD practices applied to machine learning workflows and model registries
Tips for Your Senior Mlops Engineer Job Search
Quantify your deployment impact on resumes
Recruiters for senior mlops engineer roles want numbers tied to reliability and scale. Swap vague phrases like 'improved pipelines' for specific outcomes: reduced model deployment time, increased uptime, or cut infrastructure costs by a measurable margin.
Tailor your stack to each job description
MLOps toolchains vary widely. One employer runs Kubeflow on GCP, another uses SageMaker Pipelines with Airflow. Mirror the exact tools named in the posting so your resume clears both automated filters and recruiter eyeballs on the first pass.
Apply early to roles that fit
Migrate Mate lists senior mlops engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Target postings that name your ML frameworks
Senior mlops engineers are often hired to own a specific framework ecosystem. Filter openings by the frameworks you know deepest, whether that is PyTorch serving, TensorFlow Extended, or Ray, so your application lands where you can immediately add value.
Prepare a system design answer for the interview loop
Almost every senior mlops engineer interview includes a live design session: design a feature store, a model registry, or a retraining pipeline. Practice narrating trade-offs aloud, covering observability, latency, and failure modes, not just the happy path.
Negotiate with total comp context in mind
Offers for senior mlops engineers often differ more in equity, cloud credits, and compute allowances than in base pay. Before you respond to an offer, ask explicitly what the equity vesting schedule looks like and whether a compute or tooling budget is included.
Senior Mlops Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most senior mlops engineers?
The companies hiring the most senior mlops engineers right now include Grindr, TRM Labs, and Forward Financing, with the largest share of openings in California, Massachusetts, and Georgia, based on current listings on Migrate Mate as of September 2026. Demand is especially concentrated at companies running large-scale model inference in production.
How many senior mlops engineer jobs are remote?
About 82% of senior mlops engineer openings are fully remote or hybrid as of September 2026, making it one of the more remote-accessible senior engineering roles. Model monitoring, pipeline development, and infrastructure-as-code work tend to be the sub-areas most commonly approved for fully distributed arrangements.
How do you become a senior mlops engineer?
Start by building production experience with ML pipelines, not just experimentation notebooks. Work toward owning deployment, monitoring, and retraining loops end to end. Deepen expertise in one cloud platform and one orchestration tool, then demonstrate that you can reduce manual intervention in model lifecycle management through automation and observability tooling.
Can you get hired as a senior mlops engineer without direct MLOps experience?
Yes, especially if you come from a strong DevOps or data engineering background and can show that you have applied those skills to ML systems. Employers often promote internally from ML engineering or platform engineering when a candidate understands both the software reliability side and the model lifecycle side of the role.
What does the senior mlops engineer interview process look like?
Most loops include a recruiter screen, a technical phone interview covering Python and pipeline concepts, a system design round where you architect a complete ML platform component, and a final round with cross-functional stakeholders. Some employers also include a take-home that asks you to debug or extend an existing ML workflow before the onsite stage.
Where can I find and apply to senior mlops engineer jobs?
You can find and apply to senior mlops engineer jobs on Migrate Mate, which lists current openings from across the United States. Find the roles that match your background and apply directly to each listing from the page.
See All 15 Senior Mlops Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
Find Senior Mlops Engineer Jobs