ZipRecruiter

Log In

1

Mlops Junior Jobs (NOW HIRING)

Pangram

Machine Learning Engineer (Junior)

New York, NY · On-site

$135K - $150K/yr

Pangram Labs is hiring for a strong junior Machine Learning Engineer. In this role, you will build ... Experience with MLOps and experiment tracking * Experience with DevOps tools * Familiarity with ...

New

Quince

Staff Engineer - ML Infra / MLOps

Palo Alto, CA · On-site

THE ROLE Staff Engineer for ML Infra / MLOps We are seeking a Staff ML Engineer to join our growing ... Provide deep technical mentorship to junior and mid-level engineers through design reviews, code ...

Huntington

MLOps Automation Senior Lead Engineer

Austin, TX · On-site +1

$103K - $135K/yr

The MLOps Automation Engineering Senior Lead will lead a team responsible for building and ... junior analysts regarding day-to-day activities, as necessary Proven ability to lead cross ...

Huntington

MLOps Automation Senior Lead Engineer

Houston, TX · On-site +1

$99K - $130K/yr

The MLOps Automation Engineering Senior Lead will lead a team responsible for building and ... Ability to train more junior analysts regarding day-to-day activities, as necessary * Proven ...

Huntington

MLOps Automation Senior Lead Engineer

Chicago, IL · On-site +1

$107K - $140K/yr

The MLOps Automation Engineering Senior Lead will lead a team responsible for building and ... Ability to train more junior analysts regarding day-to-day activities, as necessary * Proven ...

Huntington

MLOps Automation Senior Lead Engineer

Austin, TX · On-site +1

$103K - $135K/yr

The MLOps Automation Engineering Senior Lead will lead a team responsible for building and ... junior analysts regarding day-to-day activities, as necessary Proven ability to lead cross ...

previous pagenext page

Showing results 21-40

All JobsTechnology JobsSoftware JobsSoftware Developer JobsMlops Junior Jobs

Mlops Junior information

See salary details

$7

$26

$47

How much do mlops junior jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for mlops junior in the United States is $26.96, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $33.17 per hour, depending on experience, location, and employer.

What is an MLOps junior?

MLOps Junior roles focus on supporting the deployment, maintenance, and monitoring of machine learning models in production environments. As a junior professional, you typically assist in automating workflows, managing data pipelines, and collaborating with data scientists and engineers. Responsibilities often include configuring cloud resources, setting up CI/CD pipelines, and ensuring models run smoothly after deployment. It's an entry-level position that helps bridge the gap between data science and operations, providing hands-on experience with machine learning infrastructure.

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

To thrive as an MLOps Junior, you need a solid understanding of machine learning principles, programming in Python, and knowledge of software development practices, often supported by a degree in computer science or a related field. Familiarity with cloud platforms (such as AWS or Azure), containerization tools (like Docker), CI/CD pipelines, and version control systems (like Git) is typically required. Strong problem-solving, collaboration, and a willingness to learn stand out as soft skills in this role. These skills and qualities are crucial for efficiently deploying, maintaining, and scaling machine learning models in real-world production environments.

What are some common challenges faced by a junior MLOps professional in their first year, and how can they overcome them?

As a Junior MLOps professional, one of the main challenges is bridging the gap between data science and engineering practices, particularly when deploying machine learning models to production. You may encounter issues like automating model pipelines, managing dependencies, and ensuring reproducibility. Collaborating closely with data scientists, software engineers, and DevOps teams is essential for learning best practices and troubleshooting problems efficiently. Proactively seeking mentorship, participating in code reviews, and familiarizing yourself with popular MLOps tools (such as Docker, Kubernetes, and CI/CD platforms) can greatly accelerate your growth and confidence in the role.

What is the difference between Mlops Junior vs Data Engineer?

AspectMlops JuniorData Engineer
Required CredentialsBasic understanding of ML workflows, some certifications preferredDegree in Computer Science or related field, certifications in data management
Work EnvironmentCollaborates with data scientists and ML engineers in tech companiesWorks on data pipelines, storage, and processing systems in various industries
Industry UsageEmerging role in AI/ML teams, startups, and tech firmsEstablished role across finance, healthcare, tech, and more

The comparison shows that Mlops Junior and Data Engineer roles share some technical foundations but differ mainly in focus. Mlops Junior emphasizes deploying and maintaining ML models, while Data Engineers focus on building data infrastructure. Both roles are vital in data-driven organizations, with Mlops Junior often working closely with Data Engineers to ensure smooth ML operations.

Is MLOps a good career choice in 2026?

MLOps Junior roles are expected to remain in demand in 2026 due to the growing adoption of machine learning and AI across industries. These roles typically require skills in cloud platforms, automation, and tools like Docker and Kubernetes, making them a promising career path for those interested in AI deployment and infrastructure. Continuous learning and certification in relevant technologies can enhance job prospects in this field.

Is MLOps in high demand?

MLOps junior roles are in high demand as organizations increasingly adopt machine learning and AI solutions. These positions require skills in cloud platforms, automation, and tools like Docker and Kubernetes, reflecting the growing need for efficient deployment and management of ML models across industries.
More about Mlops Junior jobs

What cities are hiring for Mlops Junior jobs?

Cities with the most Mlops Junior job openings:

What are the most commonly searched types of Mlops jobs?

The most popular types of Mlops jobs are:

What states have the most Mlops Junior jobs?

States with the most job openings for Mlops Junior jobs include:

What job categories do people searching Mlops Junior jobs look for?

The top searched job categories for Mlops Junior jobs are:

Mlops Junior jobs near you
Infographic showing various Mlops Junior job openings in the United States as of August 2026, with employment types broken down into 95% Full Time, 1% Part Time, and 4% Contract. Highlights an 74% Physical, 10% Hybrid, and 16% Remote job distribution, with an average salary of $56,068 per year, or $27 per hour.

Machine Learning Engineer (Junior)

Pangram

New York, NY • On-site

$135K - $150K/yr

Full-time

Posted 3 days ago

New

Job description

Pangram Labs is hiring for a strong junior Machine Learning Engineer. In this role, you will build software to support the machine learning development cycle from data generation, to training models, to deployment and monitoring production machine learning systems in real customer environments.
At Pangram, ML engineers are highly involved in the research effort, are involved in publishing research, and regularly contribute ideas and innovations to the team. However, formal research experience is not necessary. This is an in-person role in our office in Downtown Brooklyn, NYC.
Responsibilities:
  • Build robust data pipelines that mine the Internet at scale and generate millions of synthetic text examples for training detection models
  • Manage distributed infrastructure for multi-GPU LLM training
  • Profiling and optimizing training and inference code
  • Deploy efficient inference pipelines for serving LLMs at scale

Requirements:
  • B.S. or M.S. in Computer Science or related areas
  • Practical experience with deep learning: internships, undergrad or masters' level research projects in an academic lab, Kaggle competitions, or interesting side projects
  • Strong programming skills in Python and modern ML frameworks
  • Excellent understanding of transformers and LLM fundamentals
  • Comfort working across research and engineering boundaries

Nice to have
  • Experience with NVIDIA GPU programming and CUDA
  • Experience with distributed training frameworks, such as DeepSpeed, FSDL, Ray
  • Experience with inference frameworks like vLLM
  • Experience with large-scale data processing (Spark, Beam) and orchestration (Airflow)
  • Experience with MLOps and experiment tracking
  • Experience with DevOps tools
  • Familiarity with cloud-based infrastructure (AWS/GCP)

Apply