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Remote Senior Machine Learning Engineer Jobs in Durham, NC

Senior Data Engineer

Raleigh, NC · Remote

$103K - $140K/yr

Implement end-to-end machine learning models and deliver stakeholder-facing analytical outputs by ... For positions with Remote-US locations, the actual salary range for the position may differ based ...

Data Engineer

Durham, NC · Remote

$150K/yr

Support and enhance enterprise MLOps capabilities and machine learning pipelines. * Enable ... remote but needs to sit in one of the following states: AL, AZ, CA, CO, CT, DE, FL, GA, HI, IL, IN ...

Senior AI Technologist

Raleigh, NC · On-site +1

$48.75 - $63/hr

Experience preparing and transforming data for analytics, machine learning, search, or AI-enabled ... Engineering or other IT-related field or equivalent experience REMOTE WORK NOTICE: This position ...

AI Automation Engineer V

Durham, NC · Remote

$126K - $244K/yr

... Sr Manager, Enterprise Systems. This is a full-time role with Avalara, offering a fully remote work ... and machine learning services and large language model integrations * Demonstrated ability to ...

AI Automation Engineer V

Durham, NC · On-site +1

$126K - $244K/yr

... Sr Manager, Enterprise Systems. This is a full-time role with Avalara, offering a fully remote work ... machine learning services and large language model integrations • Demonstrated ability to ...

Showing results 21-40

Remote Senior Machine Learning Engineer information

See Durham, NC salary details

$73K

$138.5K

$185.5K

How much do remote senior machine learning engineer jobs pay per year?

As of Sep 9, 2026, the average yearly pay for remote senior machine learning engineer in Durham, NC is $138,463.00, according to ZipRecruiter salary data. Most workers in this role earn between $118,400.00 and $156,100.00 per year, depending on experience, location, and employer.

What does a remote senior machine learning engineer do?

A Remote Senior Machine Learning Engineer designs, develops, and deploys machine learning models and systems while working from a location outside the traditional office. They collaborate with cross-functional teams, analyze large datasets, build scalable algorithms, and often mentor junior engineers. Their work helps organizations automate processes, gain insights, and improve products or services using data-driven approaches. Senior engineers are also responsible for ensuring model performance, reliability, and integration into production environments. Working remotely, they use various communication and collaboration tools to stay connected with their team.

How do remote senior machine learning engineers typically collaborate with cross-functional teams despite working remotely?

Remote Senior Machine Learning Engineers often work closely with data scientists, product managers, and software engineers using digital collaboration tools such as Slack, Jira, and video conferencing platforms. Regular virtual meetings and code reviews are standard practices to ensure alignment on project goals and to facilitate knowledge sharing. Clear communication, proactive documentation, and adaptability to different time zones are key to effective teamwork in a remote environment. This structure allows for flexibility while maintaining strong collaboration and project momentum.

What are the key skills and qualifications needed to thrive as a remote senior machine learning engineer, and why are they important?

To thrive as a Remote Senior Machine Learning Engineer, you need deep expertise in machine learning algorithms, statistical analysis, and strong programming skills (often in Python or similar languages), typically supported by a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (AWS, GCP, or Azure), and experience with data engineering pipelines are commonly required, along with certifications like TensorFlow Developer or AWS Machine Learning Specialty. Excellent problem-solving, communication, and self-management skills help you collaborate remotely, lead projects, and explain complex models to stakeholders. These skills and qualities are vital for building scalable ML solutions, ensuring effective teamwork across distributed environments, and delivering impactful results.

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

AspectRemote Senior Machine Learning EngineerRemote Data Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience with ML frameworksBachelor's/Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops and deploys ML models, collaborates with engineering teamsAnalyzes data, builds statistical models, provides insights
Employer & Industry UsageTech companies, startups, AI-focused firmsResearch institutions, tech companies, finance, healthcare

Remote Senior Machine Learning Engineers focus on designing, building, and deploying ML models, often working closely with engineering teams. Data Scientists analyze data and develop insights, but may not always deploy models. Both roles require strong technical skills and are highly sought after in tech industries, but their core responsibilities differ.

What are popular job titles related to Remote Senior Machine Learning Engineer jobs in Durham, NC?

For Remote Senior Machine Learning Engineer jobs in Durham, NC, the most frequently searched job titles are:

What job categories do people searching Remote Senior Machine Learning Engineer jobs in Durham, NC look for?

The top searched job categories for Remote Senior Machine Learning Engineer jobs in Durham, NC are:

What cities near Durham, NC are hiring for Remote Senior Machine Learning Engineer jobs?

Cities near Durham, NC with the most Remote Senior Machine Learning Engineer job openings:

AI Platform Director - Data Engineering

Raleigh, NC • On-site, Remote

$245K/yr

Full-time

Re-posted 23 days ago


First Citizens Bank rating

7.4

Company rating: 7.4 out of 10

Based on 106 frontline employees who took The Breakroom Quiz

108th of 176 rated banks


Job description

Overview

This is a remote role that may only be hired in the following location(s): North Carolina or Arizona

We are seeking an experienced Director to lead the AI platform engineering and enablement functions within our expanding Cloud Data and AI Platform organization. This role is instrumental in building, operationalizing, and governing the next-generation AI and machine learning ecosystem that powers advanced analytics and responsible AI adoption across the bank. You will own the end-to-end AI lifecycle—from data and model development to MLOps, deployment, governance, and responsible AI compliance in a regulated financial environment.

As a seasoned technology leader, you will bring your expertise in enterprise AI architecture, model operations, and platform engineering to partner with key business, technology, and governance stakeholders—ensuring AI initiatives are responsibly implemented, well-controlled, and deliver measurable value. 


Responsibilities & Qualifications

AWS AI/ML Platform Ownership

  • Architect and lead AI/ML workloads on AWS including:
    • Amazon SageMaker (training, deployment, model registry)
    • AWS Bedrock (foundation models and GenAI use cases)
    • AWS Lambda, ECS, EKS for model serving
    • S3, Glue, Snowflake for data pipelines
  • Define enterprise standards for MLOps, feature stores, and model lifecycle management
  • Build and maintain integrations with enterprise platforms for data ingestion, metadata management, tokenization, and control evidence generation. 
  • Continuously enhance the platform’s automation, resilience, and observability, ensuring robust end-to-end telemetry for both model and data pipelines. 
  • Collaborate with Enterprise Risk, Legal, Compliance, and Model Risk partners to embed Responsible AI principles and audit-ready control evidence directly into platform design. 

Machine Learning & GenAI Execution

  • Oversee development of ML models across all business units including Fraud detection systems, Credit scoring and risk modeling, Customer segmentation and personalization, Liquidity related modeling etc.
  • Lead GenAI initiatives using LLMs for Document intelligence, AI copilots etc.

 

Data & Engineering Collaboration

  • Partner with data engineering teams to ensure high-quality, governed datasets
  • Define feature engineering and data product standards in Snowflake / data lake environments
  • Integrate real-time streaming data for low-latency decision systems

 

Model Governance & Risk Compliance

  • Define and enforce standards, patterns, and guardrails for model deployment, explainability, lineage, and monitoring in alignment with enterprise risk, compliance, and security frameworks. 
  • Partner closely with leaders across Responsible AI Governance, AI Portfolio Management, AI Fluency & Engagement, and Applied Data Science & GenAI, in collaboration with enterprise risk partners, to implement a responsible AI framework that embeds audit-ready control evidence and governance mechanisms directly into the platform’s core design to ensure the platform supports scalable, ethical, compliant, and high-impact AI delivery. 
  • Implement model explainability (SHAP, LIME, interpretability frameworks)
  • Establish responsible AI policies (bias detection, fairness, auditability)

 

Team Building & Leadership

  • Develop and mentor engineering talent, championing Agile practices, continuous learning, and adoption of emerging AI and data engineering technologies. 
  • Mentor senior technical leaders and establish engineering best practices
  • Oversee technical due diligence, onboarding, and management of strategic AI and GenAI vendors and tools, ensuring compatibility with enterprise architecture and control.

Bachelor's Degree and 8 years of experience in Information Technology including application development, support roles, and management.

OR

High School Diploma or GED and 12 years of experience in Information Technology including application development, support roles, and management.

Qualifications

  • Deep hands-on experience building production ML systems on AWS
  • 2+ years in AI/ML, data science, or data engineering leadership roles
  • Strong knowledge of:
    • Machine learning (XGBoost, deep learning, NLP, time series)
    • MLOps practices (CI/CD, model monitoring, drift detection)
    • Distributed systems and cloud architecture
  • Strong programming background in Python + SQL (Scala/Java a plus)
  • Experience working in regulated environments with model governance

Preferred Qualifications

  • Experience with Generative AI / LLM platforms (Bedrock, OpenAI, Claude APIs)
  • Experience in financial services, banking, fintech, or insurance
  • Familiarity with data platforms like Snowflake, Databricks

#LI-JM1


Additional Information

Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits.

Qualifications:

Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits.

Education:UNAVAILABLEEmployment Type: FULL_TIME

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Benefits

Hours and flexibility

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