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Entry Level Machine Learning Engineer Jobs in Waco, TX

This role is the bridge between entry-level directed execution and the independence expected at the ... Commitment to continuous learning and professional development through POWERX Academy training ...

Prepare and deliver high quality instruction and facilitate the learning of students. Develop ... of programming electrical speed control systems(AC/DC Drives) Working knowledge of basic machining ...

The Maintenance Technician Apprentice is an entry-level role designed to develop foundational ... Daily On-Site Attendance. · Perform preventive and corrective maintenance on production machines ...

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Entry Level Machine Learning Engineer information

See Waco, TX salary details

$26.6K

$61.6K

$104.8K

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

As of Jul 14, 2026, the average yearly pay for entry level machine learning engineer in Waco, TX is $61,576.00, according to ZipRecruiter salary data. Most workers in this role earn between $45,700.00 and $69,700.00 per year, depending on experience, location, and employer.

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.

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 cities near Waco, TX are hiring for Entry Level Machine Learning Engineer jobs? Cities near Waco, TX with the most Entry Level Machine Learning Engineer job openings:
Infographic showing various Entry Level Machine Learning Engineer job openings in Waco, TX as of July 2026, with employment types broken down into 1% Locum Tenens, 87% Full Time, 10% Part Time, and 2% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $61,576 per year, or $29.6 per hour.
Associate to Full Professor, Tenured, Computational Materials Science, Department of Physics and Ast

Associate to Full Professor, Tenured, Computational Materials Science, Department of Physics and Ast

Baylor University

Waco, TX • On-site

Full-time

Posted 13 days ago


Baylor University rating

7.2

Company rating: 7.2 out of 10

Based on 17 frontline employees who took The Breakroom Quiz

343rd of 553 rated colleges and universities


Job description

Description
The Department of Physics and Astronomy in the College of Arts & Sciences at Baylor University invites applications for a tenured faculty position at the rank of Associate or Full Professor, effective Fall 2027. We seek an established, internationally recognized leader in computational materials science whose research integrates first-principles methods with modern informatics, artificial intelligence, and machine learning to predict, design, and understand the electronic, magnetic, optical, and topological properties of next-generation quantum materials. This position is part of a strategic cluster hire in "Novel Quantum Materials for Next-generation Electronics, Spintronics, and Optoelectronics", aligned with Baylor's Baylor in Deeds strategic plan (2024-2030), particularly its commitment to Broadening Interdisciplinary Research and Impact, and responsive to federal priorities established by the National Quantum Initiative Act and the CHIPS and Science Act. The successful candidate will help support Baylor's growing Materials Science capabilities spanning materials synthesis, advanced spectroscopic and magnetic characterization, and high-performance computation, with strong collaborative ties to faculty in Physics & Astronomy, Chemistry & Biochemistry, and the School of Engineering & Computer Science.
Position Responsibilities
We expect the successful candidate to:
• Lead an externally funded, internationally visible research program in computational/theoretical quantum materials, leveraging informatics-driven approaches (machine learning, high-throughput ab initio, data-driven discovery) alongside advanced computational methods (e.g., DFT+DMFT, GW, quantum embedding, Green's function approaches, etc.).
• Mentor graduate students and postdoctoral researchers and contribute to vibrant Ph.D. programs in Physics and Materials Science.
• Teach undergraduate and graduate courses in physics, including specialized offerings in condensed matter theory, computational physics, or quantum information science.
• Provide intellectual leadership for collaborative, multi-investigator proposals to agencies including NSF, DOE, and DoD (ARO, AFOSR, ONR, DARPA), and help shape the strategic direction of quantum materials science at Baylor.
Candidates who are outside of the United States and do not have other nonimmigrant visa status will not be sponsored for an H-1B petition.
About Baylor University: Baylor University is located in Waco, Texas and is the oldest college in the state. It has a diverse student population of 21,000 and is recognized as an R1 institution by the Carnegie Classification. Baylor is also noted on the honor roll of "Great Colleges to Work For" by ModernThink. We offer competitive salaries and benefits, allowing fauclty and staff to live in one of the fastest-growing parts of the state. As a Christian university with historic Baptist roots and as reflected in the Notice of Non-Discrimination, Baylor strives to be a place characterized by civility and respect. We believe each student, faculty, staff, and administrator is made in the image of God. Baylor's new strategic plan, Baylor in Deeds, guides the University as it continues its mission of educating men and women for worldwide leadership and service by integrating academic excellence and Christian commitment within a caring community.
Qualifications
Required Qualifications:
• Ph.D. in Physics, Applied Physics, Materials Science, or a closely related field.
• A strong record of scholarly accomplishment commensurate with appointment at the tenured Associate or Full Professor rank, including a sustained history of peer-reviewed publications in high-impact journals, and external research funding.
• Demonstrated expertise in computational or theoretical methods applied to quantum materials - for example, electronic structure theory, strongly correlated electron systems, topological matter, or quantum transport - combined with experience deploying AI/ML or related informatics methods for materials prediction, design, or analysis.
• Evidence of effective teaching, mentoring, and a commitment to collegial, interdisciplinary collaboration.
Application Instructions
Applicants should submit through Interfolio: (1) a cover letter, (2) curriculum vitae, (3) a research statement describing prior accomplishments and future plans, (4) a teaching statement, (5) a copy of the official transcript from the highest-degree granting institution (if the doctorate is in progress, a copy of the official transcript of completed doctoral hours should be submitted), and (6) the names and contact information of four professional references. All applicants must complete the self-disclosed Religious Affiliation Form in Interfolio.
All materials must be received by 11 PM Central Daylight Time on 09/15/26. Questions concerning the position should be directed to Search Committee Chair Dr. Garritt Tucker at Garritt_Tucker@baylor.edu.

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