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Machine Learning Engineer Associate Jobs in Raleigh, NC

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50 ...

Machine Learning Compiler

Raleigh, NC · On-site

$160K - $240K/yr

Engineering Group, Engineering Group > Machine Learning Engineering General Summary: Lead a team of engineers focused on advancing machine learning compiler technologies for cutting-edge AI ...

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50 ...

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50 ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Durham, NC · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Raleigh, NC · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Job Summary : Qualcomm Technologies, Inc. is focused on advancing machine learning compiler ... Required : • Bachelor's degree in Computer Science, Electrical Engineering, or related field and ...

Showing results 41-60

Machine Learning Engineer Associate information

See Raleigh, NC salary details

$40.3K

$80.3K

$128.3K

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

As of Aug 19, 2026, the average yearly pay for machine learning engineer associate in Raleigh, NC is $80,329.00, according to ZipRecruiter salary data. Most workers in this role earn between $63,700.00 and $92,300.00 per year, depending on experience, location, and employer.

What is a machine learning engineer associate?

Machine Learning Engineer Associates are entry-level professionals who help design, build, and maintain machine learning models and systems. They typically work under the guidance of senior engineers, assisting in data preprocessing, model training, and testing. Their responsibilities may include implementing algorithms, evaluating model performance, and deploying solutions to production environments. This role requires a strong foundation in programming, statistics, and machine learning principles, often acquired through education or internships.

What are some common challenges faced by machine learning engineer associates when deploying models to production?

Machine Learning Engineer Associates often encounter challenges such as ensuring model scalability, managing data pipeline reliability, and addressing issues with model drift after deployment. Collaborating closely with data engineers and software developers is essential to integrate models seamlessly into existing systems. Additionally, balancing model performance with resource constraints and maintaining clear documentation for reproducibility are important aspects of the role. Gaining familiarity with deployment tools and best practices can help overcome these hurdles.

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

To thrive as a Machine Learning Engineer Associate, you need a solid understanding of programming (especially Python), mathematics, and foundational machine learning concepts, typically supported by a relevant degree or coursework. Familiarity with tools and frameworks like TensorFlow, PyTorch, scikit-learn, and experience with version control systems such as Git are essential. Strong problem-solving abilities, communication skills, and a collaborative mindset help you work effectively within technical teams. These competencies ensure you can develop, implement, and improve machine learning models that deliver actionable insights and drive business value.

What are the most commonly searched types of Machine Learning Engineer jobs in Raleigh, NC?

The most popular types of Machine Learning Engineer jobs in Raleigh, NC are:

What cities near Raleigh, NC are hiring for Machine Learning Engineer Associate jobs?

Cities near Raleigh, NC with the most Machine Learning Engineer Associate job openings:

Infographic showing various Machine Learning Engineer Associate job openings in Raleigh, NC as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $80,329 per year, or $38.6 per hour.

Senior Machine Learning Engineer III ***Raleigh, NC***

Reed Elsevier Technology Services

Raleigh, NC • On-site

$118K - $219K/yr

Other

Posted 4 days ago


Job description

Are you looking to develop your Machine Learning Engineer career?
Do you enjoy coaching others to achieve high standards?
This is a full-time position based in Raleigh, NC.
(Hybrid - 3 days in office)
About the Role
We are seeking a Consultant-level Machine Learning Engineer to lead the implementation and scaling of AI systems for legal products. This role focuses on how to build and scale-owning system architecture, infrastructure, and productionization of ML/LLM solutions.
You will partner with Data Scientists to turn validated models and prototypes into reliable, high-performance, customer-facing systems.
Key Responsibilities
  • Architect and implement scalable ML/LLM systems in production.
  • Build and deploy LLM applications, including RAG pipelines and agentic systems.
  • Implement hybrid search systems (semantic + lexical) using embeddings and search platforms.
  • Develop and maintain APIs, microservices, and model serving infrastructure.
  • Build data pipelines and streaming systems for large-scale data processing.
  • Define and develop reusable frameworks, libraries, and infrastructure for AI/ML across teams.
  • Optimize systems for latency, scalability, reliability, and cost efficiency.
  • Establish best practices for deployment, monitoring, observability, and CI/CD.
  • Collaborate with Data Scientists to productionize models and integrate into products.
  • Provide technical leadership in system design and engineering standards.

Required Qualifications
  • Bachelor's degree in Computer Science, Engineering, or a related field.
  • Strong experience implementing and scaling production ML/LLM systems.
  • Deep experience with LLM application development, including RAG and prompt orchestration.
  • Strong experience designing and implementing agentic systems using agent frameworks (e.g., LangChain, LangGraph, AutoGen, Google ADK), including orchestration of multi-step workflows in production environments.
  • Strong experience with hybrid search (semantic + lexical), embeddings, and search platforms (e.g., Solr, OpenSearch).
  • Expertise in distributed systems and cloud-native development, including AWS (S3, DynamoDB).
  • Experience with streaming and messaging systems (e.g., Kafka, SQS) and caching (e.g., Redis).
  • Proficiency in Python and experience with systems languages (e.g., Rust, Go, Scala).
  • Experience building scalable APIs (REST/GraphQL).
  • Experience with containerization and orchestration (Docker, Kubernetes).
  • Strong software engineering fundamentals (system design, testing, CI/CD).

Preferred Qualifications
  • Experience with LLM platforms (e.g., ChatGPT/OpenAI, Claude, Gemini, LangChain, Google ADK).
  • Experience with DevOps and infrastructure as code (e.g., Terraform, CloudFormation, Jenkins).
  • Experience with big data technologies (e.g., Spark, Hadoop).
  • Familiarity with graph databases (e.g., Dgraph, Neo4j, Neptune).
  • Experience building high-availability, low-latency systems.
  • Experience in legal or regulatory domains.

Key Competencies
  • Strong system architecture and scalability mindset.
  • Ownership of implementation, performance, and reliability.
  • Ability to translate data science solutions into production systems.
  • Cross-functional collaboration with DS, product, and platform teams.
  • Excellent debugging, optimization, and operational skills.
  • Clear communication of technical designs and trade-offs.

#AIFluent
U.S. National Base Pay Range: $118,300 - $219,800. Geographic differentials may apply in some locations to better reflect local market rates.This job is eligible for an annual incentive bonus.
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