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Entry Level Machine Learning Engineer Jobs in Suwanee, GA

AVEVA Group

Software Engineering Intern

Alpharetta, GA · On-site

Clean, label, and pre-process large datasets for training and evaluating AI and machine learning ... Strong programming skills in languages such as Python, .Net/C#, SQL Familiarity with developing end ...

Aveva

Software Engineering Intern

Alpharetta, GA · On-site

Clean, label, and pre-process large datasets for training and evaluating AI and machine learning ... Strong programming skills in languages such as Python, .Net/C#, SQL Familiarity with developing end ...

Falcomm

AI/CAD Software Engineer

Atlanta, GA

Are you passionate about applying machine learning to transform the future of RF hardware? At ... We are seeking a full-time AI/CAD Software Engineer to join our team. You will lead the development ...

Pwc

US Tech - AI Engineering Senior Associate

Atlanta, GA · On-site

$55K - $187K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... PwC does not intend to hire experienced or entry level job seekers who will need, now or in the ...

Adtran

System Architecture Engineer

Atlanta, GA · On-site

Apply machine-learning techniques to analyze, predict, or optimize optical-system performance ... D. or M.Sc. in Electrical Engineering, Photonics, or a related field. Recent Ph.D. graduates are ...

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Entry Level Machine Learning Engineer information

See Suwanee, GA salary details

$27.9K

$64.6K

$109.8K

How much do entry level machine learning engineer jobs pay per year?

As of May 29, 2026, the average yearly pay for entry level machine learning engineer in Suwanee, GA is $64,559.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,900.00 and $73,100.00 per year, depending on experience, location, and employer.

What is an Entry Level Machine Learning Engineer job?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What are the key skills and qualifications needed to thrive in the Entry Level Machine Learning Engineer position, and why are they important?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are some typical projects or tasks an Entry Level Machine Learning Engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.
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Entry Level Machine Learning Engineer jobs near you
Infographic showing various Entry Level Machine Learning Engineer job openings in Suwanee, GA as of May 2026, with employment types broken down into 1% Internship, 88% Full Time, 3% Part Time, 7% Contract, and 1% Nights. Highlights an 76% Physical, 3% Hybrid, and 21% Remote job distribution, with an average salary of $64,559 per year, or $31 per hour.
AI/ML Engineer - Q126

AI/ML Engineer - Q126

R2 Technologies Corporation

Alpharetta, GA • On-site

Full-time

Posted 21 days ago

Job description

Overview:
Job Title: AI/ML Engineer
Company: R2 Technologies
Location: Alpharetta, GA (Hybrid / Remote Options Available)
Employment Type: Full-Time / Contractual
About R2 Technologies: R2 Technologies is a Certified Minority Business Enterprise (MBE) headquartered in Alpharetta, GA. With over two decades of experience across global markets, we have built a reputation as a trusted partner for IT staffing excellence and cutting-edge digital product innovation. We are driven by innovation and operate on a simple philosophy: "We deliver what we promise, and we promise only what we can deliver." Beyond providing top-tier IT talent to industries ranging from Healthcare to Financial Services, R2 builds cutting-edge proprietary solutions like SmartEnt-an Enterprise AI & IoT Intelligence Platform utilizing advanced NLP and AI technologies. By partnering closely with our clients, we deliver technology-driven outcomes that are realistic, measurable, and impactful.
Job Summary: As an AI/ML Engineer at R2 Technologies, you will be at the forefront of designing and deploying intelligent, next-generation solutions for our clients and contributing to our internal product offerings like SmartEnt. We are looking for a forward-thinking engineer who goes beyond traditional machine learning to build dynamic, agentic AI systems. You will be responsible for integrating state-of-the-art Large Language Models (LLMs)-with a strong emphasis on Anthropic's Claude-into enterprise applications. The ideal candidate deeply understands the 2026 AI ecosystem, including advanced RAG (Retrieval-Augmented Generation) architectures, autonomous agents, and model orchestration.
Key Responsibilities: * Design, develop, and deploy scalable AI/ML pipelines and autonomous agent architectures tailored to complex client business needs and R2's digital platforms.
  • Integrate and optimize cutting-edge LLMs into enterprise applications, acting as the subject matter expert on Anthropic's Claude API, its latest contextual window capabilities, and advanced reasoning features.
  • Build robust RAG systems utilizing modern vector databases to securely ground enterprise data for actionable insights and intelligent decision-making.
  • Develop agentic workflows utilizing frameworks like LangChain, LlamaIndex, or AutoGen to create systems capable of multi-step reasoning and independent tool execution.
  • Collaborate with cross-functional product and engineering teams to evaluate and implement auxiliary models when specific use cases demand them.
  • Continuously monitor, fine-tune, and evaluate model performance, ensuring low latency, high accuracy, cost-efficiency, and strict adherence to data privacy and security standards.

Qualifications: * Upto 3 years of hands-on experience in Machine Learning, AI system design, or Data Engineering.
  • Strong programming proficiency in Python and solid experience with API integrations.
  • Demonstrated experience working heavily with Anthropic's Claude (Opus/Sonnet/Haiku), including advanced prompt engineering, tool use (function calling), and fine-tuning.
  • Practical experience building agentic AI applications and a deep understanding of how to orchestrate multiple LLM agents to solve complex tasks.
  • Hands-on experience with orchestration frameworks such as LangChain or LlamaIndex.
  • Solid foundation in cloud computing environments (AWS, GCP, or Azure) to deploy scalable AI solutions.
  • Excellent problem-solving skills and the ability to translate ambiguous business requirements into robust technical architectures.

Skills:
Machine Learning,Python

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