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Junior Machine Learning Engineer Jobs in Leander, TX

PTP

Machine Learning Engineer - REMOTE

Austin, TX · On-site +1

We are looking for a Machine Learning Engineer to help us design and deliver CX solutions that provide our clients with a beautiful customer journey that achieves results. At PTP we value aptitude ...

Bumble Inc.

Senior Machine Learning Engineer

Austin, TX · On-site

$220K - $250K/yr

As a Senior Machine Learning Engineer, you'll own impactful problems end-to-end-from data exploration through to production deployment, while collaborating closely with Product, Engineering, and Data ...

Bumble Inc.

Senior Machine Learning Engineer

Austin, TX

$220K - $250K/yr

As a Senior Machine Learning Engineer, you'll own impactful problems end-to-end-from data exploration through to production deployment, while collaborating closely with Product, Engineering, and Data ...

Fluidstack

Machine Learning Engineer

Austin, TX · On-site

$224K - $279K/yr

Partner with data engineering and product pods to put predictions in the tools people already use. What We're Looking For * The below is a starting point. We always make space for exceptional people ...

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All JobsMachine Learning Engineer JobsJunior Machine Learning Engineer JobsJunior Machine Learning Engineer Jobs in Leander, TX

Junior Machine Learning Engineer information

See Leander, TX salary details

$32K

$68.6K

$104.6K

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

As of Aug 7, 2026, the average yearly pay for junior machine learning engineer in Leander, TX is $68,605.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,300.00 and $76,400.00 per year, depending on experience, location, and employer.

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

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

What kinds of projects and responsibilities can a junior machine learning engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

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

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

What does a junior machine learning engineer do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

More about Junior Machine Learning Engineer jobs
What are popular job titles related to Junior Machine Learning Engineer jobs in Leander, TX? For Junior Machine Learning Engineer jobs in Leander, TX, the most frequently searched job titles are:
What job categories do people searching Junior Machine Learning Engineer jobs in Leander, TX look for? The top searched job categories for Junior Machine Learning Engineer jobs in Leander, TX are:
What cities near Leander, TX are hiring for Junior Machine Learning Engineer jobs? Cities near Leander, TX with the most Junior Machine Learning Engineer job openings:
Junior Machine Learning Engineer jobs near you
Infographic showing various Junior Machine Learning Engineer job openings in Leander, TX as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $68,605 per year, or $33 per hour.

Sr Machine Learning Engineer( Austin only)

Autonomize Inc

Austin, TX • On-site

$103K - $142K/yr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 19 days ago

Job description

About Autonomize AI
Autonomize AI is revolutionizing healthcare by streamlining knowledge workflows with AI. We reduce administrative burdens and elevate outcomes, empowering professionals to focus on what truly matters - improving lives. We're growing fast and looking for bold, driven teammates to join us.
The Opportunity
As a Senior Machine Learning Engineer at Autonomize, you will lead the development and deployment of machine learning solutions with an emphasis on large language models (LLMs), vision models, and classic NLP (Natural Language Processing) models. The ideal candidate will have a proven track record in these areas, particularly within healthcare contexts, and will play a significant role in advancing our AI-driven healthcare optimized AI Copilots and Agents.
Key Responsibilities
  • Help fine-tune or prompt engineer large language models (LLMs) for various healthcare applications across various customer engagements.

  • Develop and refine our approach to handling vision based data using state-of-the-art VLM based models capable of processing and analyzing medical documents, healthcare forms in various formats and other visual data accurately.

  • Create and enhance classic NLP models to understand and generate human language in healthcare settings, supporting clinical documentation, and patient interaction.

  • Collaborate with multi-disciplinary teams including data scientists,ml engineers, healthcare clients, and product managers to deliver robust solutions.

  • Ensure models are efficiently deployed and integrated into healthcare systems, maintaining high performance and scalability.

  • Mentor and provide guidance to junior engineers and data scientists, fostering a culture of continuous learning and innovation.

  • Conduct rigorous testing, validation, and tuning of models to ensure accuracy, reliability, and compliance with healthcare standards.

  • Deep understanding of various training techniques including distributed training on GPUs and TPUs.

  • Stay informed on the latest research, tools, and technologies in machine learning, particularly those applicable to language and vision processing in healthcare.

  • Document methodologies, model architectures, and project outcomes effectively for both technical and non-technical audiences.

Qualifications
  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.

  • 5-7 years of experience in machine learning engineering, with a significant track record in the developing production grade models and model pipelines in a regulated industry such as healthcare.

  • Hands-on expertise in working with large language models (e.g., GPT, BERT), computer vision models, and classic NLP technologies.

  • Proficient in programming languages such as Python, with extensive experience in ML libraries/frameworks like TensorFlow, PyTorch, OpenCV, etc.

  • Strong understanding of deep learning techniques, model fine-tuning, hyper parameter optimization, and model optimization

  • Proven experience in deploying and managing ML models in production environments.

  • Excellent analytical skills, with a problem-solving mindset and the ability to think strategically.

  • Strong communication skills for articulating complex concepts to diverse audiences.

  • Working knowledge or experience in MLOps and LLMOps using tools like mlflow, kubeflow

  • Working knowledge of basic software engineering principles and best practices

  • Demonstrated working knowledge and experience on classic ML techniques and frameworks.

  • Nice to have : Knowledge of Cloud vendor based ML Platforms such as Azure ML, Sagemaker

Who you are as a person/leader
  • Owner mentality - For you, the buck stops at you, You own it, you will learn it, and you will get it done

  • You are naturally curious. Always experimenting than hypothesizing - You like to push boundaries, you figure things out and experiment your way through any problem

  • You are passionate, unafraid & loyal to the team & mission

  • You love to learn & win together

  • You communicate well through voice, writing, chat or video, and work well with a remote/global team

Nice to have competencies
  • Large/Complex organization experience in deploying NLP/ML in production

  • Experience in efficiently scaling ML model training and inferencing

  • Experience with Big Data technologies using Kafka, Spark, Hadoop, Snowflake

What We Offer
  • A chance to make a real impact in the future of healthcare

  • Autonomy, ownership, and the ability to chart your own growth path

  • Competitive compensation and benefits

  • 100% employer-paid health, vision, and dental insurance

  • Retirement plans (401k), disability insurance, employee assistance programs

How to Apply
Send your resume and a brief cover letter to careers@autonomize.ai explaining why you're the right partner for this mission.

Apply