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Full Time Mlops Engineer Jobs (NOW HIRING)

NxT Level

Lead Engineer, MLOps

Boston, MA · On-site

$111K - $146K/yr

United States Employment Type: Full-time Focus: MLOps, ML Platform, Data Science Infrastructure, AI ... Lead and grow a team of engineers across ML infrastructure, MLOps, and embedded data science ...

NxT Level

Lead Engineer, MLOps

Boston, MA

$111K - $146K/yr

United States Employment Type: Full-time Focus: MLOps, ML Platform, Data Science Infrastructure, AI ... Lead and grow a team of engineers across ML infrastructure, MLOps, and embedded data science ...

NxT Level

Lead Engineer, MLOps

Boston, MA · On-site

$111K - $146K/yr

United States Employment Type: Full-time Focus: MLOps, ML Platform, Data Science Infrastructure, AI ... Lead and grow a team of engineers across ML infrastructure, MLOps, and embedded data science ...

Jobgether

Our partner is looking for a Founding AI Platform Engineer (MLOps / Backend) based in Netherlands ... Fully remote work environment. * Full-time position within the IT function. How Jobgether works: We ...

Torc Robotics

ML Engineer, I - MLOps Framework

$132K/yr

Meet the Team As a Machine Learning Engineer on the ML Ops Framework & Conversion team, you will ... Perks of Being a Full-time Torc'r Torc cares about our team members and we strive to provide ...

Torc Robotics

ML Engineer, I - MLOps Framework

$132K/yr

Meet the Team As a Machine Learning Engineer on the ML Ops Framework & Conversion team, you will ... Perks of Being a Full-time Torc'r Torc cares about our team members and we strive to provide ...

smart folks inc

Lead AI/ML Engineer

Atlanta, GA · On-site

$98K - $129K/yr

Remote Duration: Full-time Note: Need Exceptional exp in AI/ML concepts (GenAI, Agentic, RAG ... Hands-on MLOps & Engineering Practice: * Drive the practical implementation of the MLOps strategy ...

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Full Time Mlops Engineer information

What is the difference between Full Time Mlops Engineer vs Data Scientist?

AspectFull Time Mlops EngineerData Scientist
Required CredentialsBachelor's/Master's in CS, Engineering, or related; experience with ML pipelinesBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentFocus on deploying, maintaining ML models, infrastructure, automationFocus on data analysis, model development, insights generation
Employer & Industry UsageTech companies, AI startups, enterprises with ML productsResearch institutions, tech firms, finance, healthcare

Full Time Mlops Engineers primarily focus on deploying and maintaining machine learning models in production environments, emphasizing infrastructure and automation. Data Scientists concentrate on analyzing data, developing models, and deriving insights. While both roles require a strong understanding of machine learning, MLOps engineers are more involved in the operational aspects, whereas Data Scientists focus on model creation and analysis.

Are full time MLOps engineers in demand?

Full-time MLOps engineers are in high demand due to the increasing adoption of machine learning and AI across industries. Companies seek professionals skilled in cloud platforms, automation, and tools like Docker, Kubernetes, and CI/CD pipelines to deploy and maintain ML models efficiently.

Are full time MLops engineers still in demand?

Full-time MLOps engineers are currently in high demand due to the increasing adoption of machine learning models in various industries. They are needed to develop, deploy, and maintain scalable AI systems, often requiring skills in cloud platforms, containerization, and automation tools. The role is expected to grow as organizations prioritize operationalizing AI solutions efficiently.

How much do full time MLOps engineers make?

Full-time MLOps engineers typically earn between $100,000 and $150,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in cloud platforms and automation tools can earn higher salaries, often exceeding $160,000 per year.
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Full Time Mlops Engineer jobs near you
Infographic showing various Full Time Mlops Engineer job openings in the United States as of August 2026, with employment types broken down into 93% Full Time, 3% Part Time, and 4% Contract. Highlights an 86% Physical, 5% Hybrid, and 9% Remote job distribution.

Lead Engineer, MLOps

NxT Level

Boston, MA • On-site

$111K - $146K/yr

Full-time

Re-posted 14 days ago

Job description

Technical Lead Manager, Machine Learning Operations
Location: United States
Employment Type: Full-time
Focus: MLOps, ML Platform, Data Science Infrastructure, AI-Assisted Development, Supply Chain Technology
About Our Client
Our client is building modern logistics infrastructure for the future of ecommerce.
Their platform helps brands and consumers create a better post-purchase experience by making shopping, shipping, delivery, and returns more seamless. By combining next-generation technology with a vertically integrated logistics network, our client gives ecommerce brands more control over the customer delivery experience and helps turn delivery into an extension of the brand.
The company supports millions of deliveries and partners with some of the most recognized consumer brands in the market. Their culture is high-performance, merit-based, and built for people who want to compete, win, make an impact, and help build an enduring company.
About the Role
Our client is hiring a Technical Lead Manager, Machine Learning Operations to own the Data Science platform and lead the roadmap for building a more sophisticated, stable, and scalable ML infrastructure foundation.
This person will lead a team focused on ML infrastructure, ML operations, and embedded data science engineering. The team partners closely with data scientists to ensure forecasting, network orchestration, pricing, routing, and other machine learning systems are well-designed, production-ready, and built to scale.
This is a hands-on leadership role. You'll manage and grow the team while still contributing technically through architecture, code, design reviews, roadmap ownership, and setting the engineering bar.
What You'll Do
  • Lead and grow a team of engineers across ML infrastructure, MLOps, and embedded data science project work
  • Own the 1-2 year roadmap for improving the company's ML platform and operations research infrastructure
  • Standardize and improve training infrastructure, serving infrastructure, deployment pipelines, monitoring, permissions, environments, and service operations
  • Embed engineers into major science initiatives across forecasting, network orchestration, pricing, routing, and supply chain optimization
  • Help ensure data science projects are production-ready from day one
  • Build templates, patterns, and platform standards that help new ML systems get up and running quickly
  • Partner closely with data science, engineering, developer experience, and platform teams
  • Drive adoption of AI-assisted and agentic development workflows across the Data Science organization
  • Set standards for using AI in EDA, model iteration, ML/OR methodology, and development velocity
  • Review designs, write code, improve technical quality, and raise the bar for production ML systems
  • Participate in the on-call rotation for production data science systems

What We're Looking For
  • Bachelor's degree with 6+ years of Machine Learning Engineering experience, or Master's degree with 4+ years of Machine Learning Engineering experience
  • Experience leading or managing high-velocity ML platform, MLOps, or ML infrastructure teams
  • Strong hands-on experience building production ML systems
  • Experience with ML platforms, including training infrastructure, serving infrastructure, feature stores, orchestration, monitoring, and deployment pipelines
  • Strong Python experience
  • Experience driving AI-assisted or agentic tooling adoption inside an engineering or data science organization
  • Strong knowledge of cloud-based data engineering and data science tools, preferably AWS
  • Experience with data warehouses such as Redshift, Databricks, Snowflake, or similar platforms
  • Experience with open-source large-scale ML tooling such as Ray, Flink, Feast, or similar technologies
  • Ability to balance short-term business impact with long-term platform vision
  • Strong communication skills and a business-value-first approach to technical work

Bonus Experience
  • Experience building ML systems in logistics, ecommerce, supply chain, transportation, marketplaces, or operations-heavy businesses
  • Experience supporting forecasting, routing, pricing, network optimization, or operations research systems
  • Experience partnering directly with data science teams to productionize models
  • Experience building reusable ML templates, internal platforms, or service creation frameworks
  • Experience improving developer experience or AI-assisted development workflows

Why This Opportunity
  • Lead the platform foundation behind high-impact data science systems
  • Work on machine learning problems tied directly to real-world logistics, delivery, pricing, forecasting, and network orchestration
  • Manage and grow a technical team while staying hands-on
  • Own a meaningful roadmap for ML infrastructure at scale
  • Help drive AI-assisted development adoption across a data science organization
  • Build systems that power millions of package decisions and help major ecommerce brands deliver better customer experiences
  • Join a high-performance team with strong growth potential and meaningful equity upside

Apply