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Entry Level Machine Learning Jobs in Duluth, GA (NOW HIRING)

PrizePicks

Data Engineer

Atlanta, GA · On-site +1

$105K - $140K/yr

... machine learning, and business decision-making at PrizePicks. This is an entry-level role where you will work on well-defined pipeline and data tasks under guidance, building your skills across the ...

84 Lumber Company

Manager Trainee

Winder, GA · On-site

The Manager Trainee is a full-time, entry-level position designed to prepare you for a leadership ... Manager Trainees must complete the learning plan and course of study as outlined within the ...

U-Haul

Hitch Installer / Entry Level Mechanic

Atlanta, GA

$20.75 - $27.75/hr

Are you interested in learning valuable technical skills? U-Haul is seeking a hard-working ... parts, machines, fumes, or irritating chemicals. May be required to use protective clothing, or ...

U-Haul

Hitch Installer / Entry Level Mechanic

Atlanta, GA · On-site

$20.75 - $27.75/hr

Are you interested in learning valuable technical skills? U-Haul is seeking a hard-working ... parts, machines, fumes, or irritating chemicals. May be required to use protective clothing, or ...

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Entry Level Machine Learning information

See Duluth, GA salary details

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How much do entry level machine learning jobs pay per hour?

As of Jul 13, 2026, the average hourly pay for entry level machine learning in Duluth, GA is $16.07, according to ZipRecruiter salary data. Most workers in this role earn between $14.38 and $17.50 per hour, depending on experience, location, and employer.

What types of projects can an entry-level machine learning professional expect to work on in their first year?

As an entry-level machine learning professional, you’ll typically start by supporting more senior data scientists and engineers with tasks such as data cleaning, exploratory data analysis, and building baseline models. You may work on pilot projects like developing recommendation systems, automating simple classification tasks, or contributing to model evaluation and performance tuning. Collaboration with cross-functional teams—including software engineers, product managers, and domain experts—is common, providing valuable exposure to real-world business problems and laying a foundation for more complex responsibilities as you gain experience.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or data science executives, often requiring advanced skills, extensive experience, and specialized knowledge. These positions usually involve leadership, strategic planning, and the development of complex AI systems, and they tend to be found in large tech companies or specialized AI firms.

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

To thrive as an Entry Level Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially in Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow or PyTorch, version control systems like Git, and data analysis libraries is commonly required. Strong problem-solving abilities, curiosity, and effective communication skills help differentiate candidates in collaborative and fast-evolving environments. These skills and qualifications are essential for building, testing, and improving machine learning models that drive innovation and business value.

What is the difference between Entry Level Machine Learning vs Data Analyst?

AspectEntry Level Machine LearningData Analyst
Required CredentialsBachelor's in CS, Math, or related; some knowledge of programming and statisticsBachelor's in Statistics, Math, or related; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentTech companies, startups, research labs; focus on developing models and algorithmsBusiness, finance, marketing; focus on interpreting data and generating reports
Employer & Industry UsageTech, e-commerce, healthcare; roles involve building predictive modelsRetail, finance, consulting; roles involve analyzing data trends and insights

Entry Level Machine Learning roles focus on developing algorithms and models using programming and statistical skills, often in tech-driven environments. Data Analysts interpret and visualize data to support business decisions, typically using tools like Excel and SQL. While both roles require analytical skills, Machine Learning positions emphasize coding and model development, whereas Data Analysts focus on data interpretation and reporting.

Which 3 jobs will survive AI?

Entry level machine learning roles are likely to persist as they require specialized knowledge in data analysis, programming, and domain expertise that AI tools currently cannot fully replicate. Jobs involving complex problem-solving, creativity, and human interaction, such as data scientists, AI ethics specialists, and AI system trainers, are also expected to remain in demand. Developing skills in programming languages like Python and understanding of algorithms will enhance job security in this field.

How to get into machine learning with no experience?

Entry level machine learning roles typically require foundational knowledge in programming, mathematics, and data analysis. Gaining skills through online courses, tutorials, and practicing with projects using tools like Python and libraries such as scikit-learn or TensorFlow can help build a portfolio. Earning certifications or completing relevant coursework can also improve job prospects for beginners.

What are entry level machine learning jobs?

Entry level machine learning jobs are positions designed for individuals just starting their careers in the field of machine learning. These roles typically involve working on data preparation, building and testing basic models, and assisting senior data scientists or engineers. Common job titles include Machine Learning Engineer, Data Analyst, or Junior Data Scientist. Requirements often include proficiency in programming languages such as Python, foundational knowledge of statistics, and experience with machine learning libraries. These jobs provide hands-on experience and mentorship to help new professionals grow their skills.

What Are Entry-Level Machine Learning Jobs?

Entry-level machine learning jobs focus on creating and using software for the development of artificial intelligence (AI). In this role, you may help program computer software, engineer mechanical solutions, help develop learning objectives, and use analytics to determine whether or not the technology created is meeting development goals. Many entry-level machine learning jobs focus on particular parts of the industry. For example, some companies focus on surveillance and intelligence, while others are creating technology for self-driving vehicles. Employers often use this position as a type of extended learning period to help you develop your skills before you start taking responsibility for major projects.

What jobs pay $4000 a week without a degree?

Entry-level machine learning roles typically do not pay $4000 a week without advanced skills or certifications. High-paying tech jobs often require specialized knowledge, experience, or degrees, but some freelance data scientists or AI consultants with strong portfolios can reach high earnings through project-based work. Most roles at this pay level generally demand experience or advanced training beyond entry-level positions.
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Entry Level Machine Learning jobs near you
Computer Programmer AI and ML

Computer Programmer AI and ML

R2 Technologies Corporation

Alpharetta, GA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 23 days ago

Job description

Overview:
Technologies are evolving at a rapid pace, with innovation being driven by advancements in technology itself. Today, information technology is at a crossroads, poised to reach unprecedented levels, as evidenced by substantial investments from large companies amounting to billions of dollars. R2 Technologies is aligning with this change by forming a team dedicated to training professionals from basic to advanced levels.
Do you have a passion for integrating AI and deep learning into the next generation of software development? Do you want to be part of our journey? R2 Technologies is currently seeking motivated, career-oriented, and client-focused Software Engineers specializing in AI and data science. The ideal candidates will have a strong ability to identify and communicate patterns in data and model behavior. In this role, you may collaborate with multiple teams and technologies (machine learning, quality assurance, cloud infrastructure support, user studies) to improve algorithm quality and guide feature development with a data-driven approach, delivering outstanding computer experiences.
Led by Dr. Raju Manthena, CEO of R2 Technologies, we are building a team to provide customers with the most innovative technology services as efficiently as possible. Our core technology prototypes will feature customizable algorithms designed to meet the needs of various industries, including medical, clinical, pharmaceutical, financial, and insurance sectors.
Required Knowledge, Skills and Abilities
  • Ability to lean and write code in SQL, R, or Python for processing large datasets in distributed cloud environments, and learn and adapt in processing and analyzing healthcare data.
  • learn and practice developing, evaluating, and implementing machine learning models.
  • learn and practice in working with clients across disciplines to develop approaches for use in their business core.
  • learn and practice in working in cloud environments .
  • Graduate level understanding of techniques in machine learning, knowledge representation, and artificial intelligence along with a strong understanding of statistics.
  • Knowledge of software development, machine learning, and technology infrastructure
  • Excellent verbal and written communication skills, strong interpersonal skills, along with demonstrated creativity and latitude in problem solving, including the ability to prioritize and execute multiple competing tasks.

Responsibilities include but are not limited to:
  • Research and evaluate emerging AI, data science, and related technologies, such as Generative AI, technical tools and approaches for responsible and trustworthy AI, Quantum, Image Compression and Recall, and Self Supervised Learning.
  • Stay current on published state-of-the-art data science, AI, and analytics methods and applications and seek out opportunities to apply them against client use cases.
  • Develop statistical and advanced analytics models using advanced analytic techniques such as Natural Language Processing, Graph Analytics, Computer Vision, modeling and simulation, Operations Research, anomaly detection, data visualization and metrics creation.
  • Direct and actively contribute to proof-of-concept studies and research prototypes, including creating prototypes to implement data models.
  • Perform knowledge elicitation from client business problems and understanding and convert that to derived algorithms, and lead and guide teams in this knowledge elicitation process.
  • Apply design thinking or other solution-based methods to solve problems consisting of various qualitative activities that support the generation of insightful, human-centered and impactful design solutions.
  • Identify AI challenges in non-AI projects to enhance the capabilities of data scientists by automating repetitive tasks, uncovering patterns, and providing advanced analytics and predictive modeling techniques.
  • Translate technical requirements to agile tasks to prioritize models and data according to the goals and requirements of the client.
  • Perform solution development through white boarding sessions - Algorithmic problems, data manipulation tasks, or other technical challenges related to data science.
  • Communicate findings to diverse technical and non-technical stakeholders, and engage clients to distill complex technical language. Communicate these findings in language and forms appropriate for the full spectrum of technical background and focus, from end users through executive decision makers.
  • Lead and mentor entry-level, mid-level, and senior level practitioners of AI and data science.
  • Shape Internal Research & Development (IRAD) directions in AI, data science, and related scientific areas. Ensure that these directions are aligned with the practice strategy and client needs.
  • Represent ManTech's data and AI practice in the broader community. Example activities include conference participation, formal or information publications, and speaking at client events.

Qualifications:
• Bachelor's degree in computer science, Engineering, or related field. Good to have Master and or Ph.D.
What we offer : The best in the industry -
  1. Medical insurance
  2. Dental
  3. Vision
  4. Life Insurance
  5. 401K with employer contribution
  6. Paid vacation
  7. Immigration sponsorship for those who requires it - (H1 B and Green cord)
  8. Career guidance
  9. Employee referral bonus
  10. Project based - performance allowances.

Skills:
SQL, Spark, and Python,AI,ML

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