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Machine Learning Engineer Hybrid Jobs (NOW HIRING)

XPO

Machine Learning Engineer - Hybrid

Boston, MA

$100K - $120K/yr

What you'll need to succeed as a Machine Learning Engineer at XPO Minimum qualifications: * Bachelor's degree in Computer Science, Engineering, or related field, or equivalent related work or ...

XPO

Machine Learning Engineer - Hybrid

Boston, MA · On-site

$100K - $120K/yr

What you'll need to succeed as a Machine Learning Engineer at XPO Minimum qualifications: * Bachelor's degree in Computer Science, Engineering, or related field, or equivalent related work or ...

Manulife Financial

$150 - $200/hr

Senior Machine Learning Engineer Job Duties Package models, automate workflows, and operationalize ... Hybrid from Boston office (3 days from office, 2 days from home) Minimum Requirements Master ...

3B Staffing LLC

Machine Learning Engineer

Tahoma, CA · On-site

Hybrid - Bay Area, CA We are seeking a Machine Learning Engineer with expertise in molecular design to support cutting-edge drug discovery initiatives. The role focuses on developing and optimizing ...

3B Staffing LLC

Machine Learning Engineer

Tahoma, CA · On-site

Hybrid - Bay Area, CA We are seeking a Machine Learning Engineer with expertise in molecular design to support cutting-edge drug discovery initiatives. The role focuses on developing and optimizing ...

AI Squared

Machine Learning Engineer

Washington, DC · On-site

Machine Learning Engineer Washington, DC (Hybrid) About the Role: We are seeking a highly skilled Machine Learning Engineer to join our core AI team. In this role, you will focus on deploying ...

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All Jobswork remotely one day a week JobsTechnology JobsData JobsData Scientist JobsMachine Learning Engineer Hybrid Jobs

Machine Learning Engineer Hybrid information

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$31.5K

$128.8K

$193.5K

How much do machine learning engineer hybrid jobs pay per year?

As of Sep 7, 2026, the average yearly pay for machine learning engineer hybrid in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What is the difference between Machine Learning Engineer Hybrid vs Data Scientist?

AspectMachine Learning Engineer HybridData Scientist
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with ML frameworksBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops, tests, deploys ML models; collaborates with engineering teamsAnalyzes data, builds models, interprets results; works across departments
Industry UsageTech, finance, healthcare, e-commerceResearch, finance, marketing, tech

Machine Learning Engineer Hybrid focuses on developing and deploying ML models within engineering environments, often requiring coding and deployment skills. Data Scientists analyze data, build models, and interpret results, often in research or strategic roles. While both roles require strong analytical skills and knowledge of ML, the Engineer Hybrid emphasizes deployment and integration, whereas Data Scientists focus on data analysis and insights.

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Cities with the most Machine Learning Engineer Hybrid job openings:

What states have the most Machine Learning Engineer Hybrid jobs?

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Machine Learning Engineer Hybrid jobs near you
Infographic showing various Machine Learning Engineer Hybrid job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.

Sr. Machine Learning Engineer - Hybrid schedule

Calance US

Los Angeles, CA • Hybrid

$112K - $154K/yr

Full-time

Medical, Dental, Vision, Life

Posted 13 days ago

Job description

We are hiring Sr. Machine Learning Engineer - Hybrid schedule for a Full Time position in Los Angeles or NYC, CA
Sr. Machine Learning Engineer
About the Role
The Senior Machine Learning Engineer is an integral part of the Technology & Information Services team. This role will be responsible for the design, deployment, and optimization of custom workflows using classical machine learning (ML), Natural Language Processing (NLP), and Generative AI techniques to enhance legal and business processes, while designing, building, and optimizing custom machine learning models and workflows to optimize legal and business workflows. This role will be located in our Global Services Office. Please note that this role may be eligible for a flexible working schedule that allows for a hybrid and in-office presence.
Responsibilities & Qualifications
Other key responsibilities include:
Contributing to the entire lifecycle of AI/ML applications including concept, design, test, release, and support
Developing and maintaining robust ML pipelines for training, validation, and model deployment
Working with DevOps or infrastructure teams to manage GPU resources, model serving frameworks, and CI/CD workflows
Evaluating and integrating new research, tools, and frameworks to advance the team s capabilities
Developing ML/GenAI solutions in a professional manner, and in accordance with established deliverable schedules and firm procedures
Protecting and maintaining any highly sensitive, confidential, privileged, financial, and/or proprietary information that retains
We d love to hear from you if you:
Demonstrate proficiency with Python including experience with libraries and frameworks relevant to GenAI application development (e.g., LangChain)
Exhibit proficiency with ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn), and serving tools (e.g., TorchServe, ONNX, Triton)
Display proficiency in training or fine-tuning language models (e.g., BERT, Llama2, GPT), and their optimization (LoRA, knowledge distillation, pruning, and quantization)
And have:
A bachelor s degree and master s degree in information systems, computer science, engineering, data science, or a related field, preferably
A minimum of five (5) years of experience in industry roles focused on machine learning, applied AI, or data science
A minimum of five (5) years of Python industry experience
A minimum of three (3) years of experience working with agile teams
Experience building and productizing ML models and systems
Estimated Pay Range: 175-195K