Is on LinkedIn?
Job not on LinkedIn
🕒 Yesterday
Job not on LinkedIn
MLOps Engineer operating scalable ML infrastructure for SumerSports’ football intelligence platform. Building production pipelines, model serving systems, observability, security, and cloud automation.
AWS
Azure
Cloud
Google Cloud Platform
GRPC
Kubernetes
Python
Spark
🕒 2 days ago
Databricks MLOps Engineer building cloud-native AI and data infrastructure for Solvd, an enterprise technology consulting firm. Developing ML pipelines, LLM integrations, infrastructure-as-code, and observability systems.
🌐 Argentina, Ukraine, +4 more countries – Remote
⏰ Full Time
🟠 Senior
🔴 Lead
🤖 Machine Learning Engineer
AWS
Cloud
Docker
Python
TypeScript
🕒 2 days ago
Senior MLOps Engineer building production ML infrastructure for Hungryroot’s AI-powered grocery recommendations and personalization. Operating Python, AWS, Databricks, Spark, and model lifecycle systems.
🇺🇸 United States – Remote
💵 $170k - $210k / year
⏰ Full Time
🟠 Senior
🤖 Machine Learning Engineer
🦅 H1B Visa Sponsor
AWS
Docker
Jenkins
Python
Spark
SQL
Terraform
Unity
Job not on LinkedIn
🕒 3 days ago
Job not on LinkedIn
Senior DevOps/MLOps Engineer operating SimpliGov’s Azure AI platform for government customers. Building secure Kubernetes infrastructure, compliant inference paths, observability, releases, and cost controls.
Azure
Cloud
Kubernetes
Microservices
Terraform
Job not on LinkedIn
🕒 6 days ago
Job not on LinkedIn
Senior MLOps Engineer building production ML and generative AI infrastructure for Lyra Health, an evidence-based mental healthcare provider. Developing platforms, evaluation frameworks, and AI product services.
🇺🇸 United States – Remote
💵 $143k - $197k / year
💰 $235M Series F on 2022-01
⏰ Full Time
🟠 Senior
🤖 Machine Learning Engineer
🦅 H1B Visa Sponsor
AWS
Cloud
Docker
Java
Kotlin
Kubernetes
Python
🕒 August 4
Senior MLOps Engineer scaling platforms, workflows, and governance for Oura’s connected health-tracking products. Enabling reliable machine-learning development, deployment, and operations across distributed data science teams.
🐻 Alaska, Iowa, +6 more states – Remote
💵 $147.9k - $203k / year
⏰ Full Time
🟠 Senior
🤖 Machine Learning Engineer
AWS
Cloud
🕒 August 4
Lead MLOps engineer scaling TetraScience’s scientific data and AI cloud platform. Architecting multi-tenant model serving, LLM workflows, evaluation, security, and observability for pharmaceutical customers.
🏄 California, Massachusetts – Remote
💵 $200k - $270k / year
⏰ Full Time
🟠 Senior
🏗️ Platform Engineer
🦅 H1B Visa Sponsor
AWS
Cloud
Docker
Python
TypeScript
Job not on LinkedIn
🕒 August 4
Job not on LinkedIn
LLMOps Engineer evaluating AI learning products for ALX Africa, a nonprofit digital skills training organisation. Building regression suites, analysing LLM data, and reporting model behaviour across cross-functional teams.
Python
🕒 July 31
Senior MLOps Engineer at Nublit designing scalable AI platforms with Docker and Kubernetes. Involves CI/CD pipeline development and collaboration with cross-functional teams.
🗣️🇪🇸 Spanish Required
Docker
Kubernetes
Linux
Python
Terraform
Job not on LinkedIn
🕒 July 29
Job not on LinkedIn
MLOps Engineer at EXL Services developing machine learning solutions remotely in India. Requires expertise in Python, AWS, and ML lifecycle management.
🇮🇳 India – Remote
💰 $2M Venture Round on 2015-01
⏰ Full Time
🟢 Junior
🟡 Mid-level
🤖 Machine Learning Engineer
AWS
Docker
EC2
Flask
PySpark
Python
SQL
Job not on LinkedIn
🕒 July 29
Job not on LinkedIn
MLOps Engineer leveraging JAX, PyTorch, and GPU kernel programming. Contributing to next-generation AI systems with a focus on distributed training and ML infrastructure.
🇺🇸 United States – Remote
💵 $70 - $110 / hour
⏳ Contract/Temporary
🟢 Junior
🟡 Mid-level
🤖 Machine Learning Engineer
PyTorch
🕒 July 28
Technical Lead Manager overseeing Machine Learning Operations for Veho's data science platform. Driving AI development and managing a team of engineers to enhance data science capabilities.
🏄 California – Remote
💵 $199k - $241k / year
💰 $170M Series B - Veho on 2022-02
⏰ Full Time
🟠 Senior
🧑💻 Full-stack Engineer
Amazon Redshift
AWS
Cloud
Python
Ray
🕒 July 28
Senior Machine Learning Operations Engineer at Veho, building infrastructure for AI/ML capabilities to enhance logistics and customer experience.
🏄 California – Remote
💵 $175k - $200k / year
💰 $170M Series B - Veho on 2022-02
⏰ Full Time
🟠 Senior
🤖 Machine Learning Engineer
Amazon Redshift
AWS
Cloud
Python
Ray
SQL
Job not on LinkedIn
🕒 July 28
Job not on LinkedIn
Staff MLOps Engineer focused on building scalable infrastructure for deploying AI/ML systems in a mission-driven company. Working with LLMs, ensuring compliance and driving AI reliability.
Docker
Kubernetes
Terraform
Job not on LinkedIn
🕒 July 28
Job not on LinkedIn
Senior MLOps Engineer at TRM Labs focusing on building and scaling AI/ML infrastructure. Responsible for deploying models and ensuring reliability in a fast-paced environment.
Docker
Kubernetes
Prometheus
Python
Terraform
Job not on LinkedIn
🕒 July 28
Job not on LinkedIn
MLOps Engineer at Sequen, building and scaling critical AI systems for machine learning operations. Focused on infrastructure and ensuring optimized model serving in production environments.
AWS
Azure
Cloud
Distributed Systems
Docker
Google Cloud Platform
Kubernetes
Python
PyTorch
Job not on LinkedIn
🕒 July 21
Job not on LinkedIn
Senior MLOps Engineer turning models into reliable services for Zeitview, an intelligent aerial imaging company. Working on infrastructure, pipelines, and tooling for production-grade deployments.
🍂 Massachusetts – Remote
💵 $170k - $180k / year
💰 $55M Series E on 2023-02
⏰ Full Time
🟠 Senior
🤖 Machine Learning Engineer
AWS
Cloud
Docker
GraphQL
Kubernetes
Postgres
Python
Terraform
Job not on LinkedIn
🕒 July 21
Job not on LinkedIn
Senior MLOps Engineer turning ML models into reliable, production-grade services at Zeitview. Collaborating with scientists and engineers on infrastructure, pipelines, and automation initiatives.
🏄 California – Remote
💵 $170k - $180k / year
💰 $55M Series E on 2023-02
⏰ Full Time
🟠 Senior
🤖 Machine Learning Engineer
AWS
Cloud
Docker
Kubernetes
Python
Terraform
Job not on LinkedIn
🕒 July 21
Job not on LinkedIn
Senior MLOps Engineer turning ML models into reliable, production-grade services at Zeitview. Collaborating with scientists and engineers on infrastructure, pipelines, and automation initiatives.
🏄 California – Remote
💵 $170k - $180k / year
💰 $55M Series E on 2023-02
⏰ Full Time
🟠 Senior
🤖 Machine Learning Engineer
AWS
Cloud
Docker
Kubernetes
Python
Terraform
+41 More MLOps Engineer Jobs Available!
The average salary for remote mlops engineers is $159,279 per year. This is based on data from 175 job openings. Our advanced AI searches the internet for remote job openings and posts them on our website. We use the salary data from these job postings to calculate salary expectations.
Below is a breakdown of salary data by years of experience:
| Experience | Number of roles analyzed | Average Salary |
|---|---|---|
🟢 Junior MLOps Engineer (1-2 yrs) | 9 | $128,238 |
🟡 Mid-level MLOps Engineer (2-4 yrs) | 76 | $148,978 |
🟠 Senior MLOps Engineer (5-9 yrs) | 71 | $161,200 |
🔴 Lead MLOps Engineer (10+ yrs) | 19 | $208,008 |
We analyzed 138 job listings in the last year and found it takes about 44 days for employers to close a job opening.
We reviewed 175 job postings and found the top 10 skills employers are asking for most often are:
You need strong programming skills in Python or R, expertise in machine learning frameworks like TensorFlow or PyTorch, proficiency in cloud services (AWS, Azure, GCP), and knowledge of CI/CD practices. Familiarity with data pipelines, containerization (Docker, Kubernetes), and strong problem-solving skills are also important.
Typically, a degree in computer science, data science, or a related field is required. Experience with machine learning projects and a strong portfolio of work are often more important than formal education. Certifications in cloud platforms and MLOps methodologies can enhance your qualifications.
Responsibilities include deploying machine learning models, automating workflows, monitoring model performance, collaborating with data scientists and developers, and ensuring scalability and reliability of ML applications. You'll also need to maintain data integrity and adherence to best practices.
Benefits include flexibility in work hours, the ability to work from diverse locations, reduced commuting costs and time, and an enhanced work-life balance. Remote roles also provide opportunities to work with cutting-edge technologies and collaborate with a global talent pool.
We scan the internet everyday and find jobs not posted on LinkedIn or other job boards.
We find jobs as soon as they're posted, so you can apply before everyone else.
Most members hear back within the first week
We find jobs other job boards miss.
