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Entry Level Machine Learning Jobs in Austin, TX (NOW HIRING)

We are currently seeking an entry level Graduate Engineer- Electrical with 0-2 years of experience ... Prior experience or knowledge of coding and/or machine learning technologies * Applicants must be ...

We are currently seeking an entry level Graduate Engineer- Electrical with 0-2 years of experience ... Prior experience or knowledge of coding and/or machine learning technologies * Applicants must be ...

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Entry Level Machine Learning information

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

As of Jun 9, 2026, the average hourly pay for entry level machine learning in Austin, TX is $17.31, according to ZipRecruiter salary data. Most workers in this role earn between $15.48 and $18.85 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 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.

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 are the most commonly searched types of Machine Learning jobs in Austin, TX? The most popular types of Machine Learning jobs in Austin, TX are:
What are popular job titles related to Entry Level Machine Learning jobs in Austin, TX? For Entry Level Machine Learning jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Entry Level Machine Learning jobs in Austin, TX look for? The top searched job categories for Entry Level Machine Learning jobs in Austin, TX are:
What cities near Austin, TX are hiring for Entry Level Machine Learning jobs? Cities near Austin, TX with the most Entry Level Machine Learning job openings:
Jr java full stack developer/Data scientist

Jr java full stack developer/Data scientist

SynergisticIT

Austin, TX

Full-time

Posted 22 days ago


Job description

Job Search Feeling Like Guesswork? Applied to 200+ Jobs and Still No Interviews? Applied Everywhere?

Still No Interviews or Offers? Get Hired with a Process! Many job seekers assume the tech market has shut down, but the truth is companies are still hiring — they're just being more selective.

That means only the most prepared, polished, and employer‐ready candidates get through.If you've sent out hundreds—maybe thousands—of applications and your inbox is still silent, it doesn't mean you're not capable. It usually means your profile isn't lining up with how companies filter, shortlist, and interview candidates right now. In today's market, employers expect more than a degree or a few tutorial projects.

They want candidates who look job-ready on paper, sound confident in interviews, and demonstrate hands-on ability in the tools teams actually use. That's exactly what SynergisticIT solves—because the real challenge isn't learning in isolation. The real challenge is translating learning into interviews and offers.

Since 2010, SynergisticIT has helped thousands of candidates secure full-time roles with leading companies and recognizable brands—think Google, Apple, PayPal, Visa, Western Union, Wells Fargo, Client, Walmart Labs, Client, Banking, Client, Wayfair, and many more—often in the $95k to $154k offer range depending on role, location, and skillset. The purpose of SynergisticIT is simple: close the gap between what you know and what employers expect you to prove. Here's the truth employers hire based on whether you can handle real work—clean coding, debugging, teamwork workflows, version control, APIs, cloud basics, deployment pipelines, and the ability to explain what you did.

That's why SynergisticIT emphasizes structured skill-building, project depth, resume positioning, interview readiness, and support through the job-search process. What roles are in demand right now? A lot of jobseekers assume they must become "AI experts” overnight.

Not true. Many companies are actively hiring professionals in core roles that run modern software teams. In JOPP, the demand typically includes roles such as entry-level software programmer, Java full stack developer, Python/Java developer, data analyst, data engineer, data scientist, and machine learning/AI engineer.

In other words, SynergisticIT focuses on building candidates across Java / Full Stack / DevOps and Data Analytics / Data Engineering / Data Science / ML/AI based on what employers repeatedly request. Who benefits most from this model? If you're applying and not seeing results, you're likely in one of these situations: You have skills, but your resume doesn't show impact and your projects look generic You know tools, but you can't explain them confidently in interviews You've learned from courses, but you lack real-world structure and job alignment You've built a portfolio, but it doesn't match what hiring managers evaluate SynergisticIT works especially well for candidates such as: recent grads in CS/Engineering/Math/Stats, jobseekers who were laid off and need an updated stack, career switchers who want a guided plan, candidates with career gaps, people with "learning but not hired” bootcamp history, experienced professionals not landing interviews, and international candidates on F1/OPT needing a clear employment pathway.

SynergisticIT also supports candidates with guidance around STEM extension, and provides process support for H-1B and Green Card filing once employed (as applicable through employers and standard processes). If you want to explore here are the key links: Event videos (OCW, JavaOne, Gartner): USA Today feature Client JOPP: Job Placement Program Contact Us https://www.synergisticit.com/contact-us/ You don't need more random applications. You need a job-ready plan.

Start smarter—start with the right support. Please read our blogs Why do Tech Companies not Hire recent Computer Science Graduates | SynergisticIT What Recruiters Look for in Junior Developers | SynergisticIT Software engineering or Data Science as a career? Please note: Resume databases are shared with clients and interested clients will reach out directly if they find a qualified candidate for their req.

Resume submissions may be shared with our JOPP team database also. Please unsubscribe if contacted or if you don't want to be contacted please don't submit your resume.