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Entry Level Machine Learning Engineer Jobs in Dallas, TX

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 ...

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 ...

Develop and optimize machine learning and deep learning models using frameworks like TensorFlow or PyTorch. * Strong skills in programming languages such as Python, R, or Java, essential for ...

Lead Research Engineer

Frisco, TX · On-site +1

$95.90K - $126.40K/yr

We hire engineers and specialists across a variety of AI research areas to drive the company ... Experienceintegrating Machine Learning solutionsinto production-grade softwarewith a sound ...

Bigdata Engineer

Plano, TX · On-site

$52 - $69/hr

... machine learning engineering • Exposure to NLP and text processing • Experience with pipelines, job scheduling and workflow management Personal Skills • Experienced in managing work with ...

Ability to understand, apply,integrateand deploy Machine Learning capabilities and techniques into other systems. * Familiarity with the Python data science stack through exposure to libraries such ...

AI/ML Engineer

Irving, TX · On-site

$77.40K - $135.40K/yr

Design and deploy machine learning models, Agentic AI systems, and LLM-based applications ... Collaborate with engineers, data scientists, product stakeholders, and platform teams to deliver ...

AI Developer

Mckinney, TX · On-site

$100K - $130K/yr

... Engineering, Agentic AI • Knowledge of advanced statistical/machine learning techniques ... Machine Learning & Advanced Analytics • Build, train, tune, and deploy machine learning models ...

Experience with machine learning libraries and algorithms such as PyTorch. * Experience with machine learning data preparation concepts (cross validation, folding, boosting, feature engineering) with ...

Experience with machine learning libraries and algorithms such as PyTorch. * Experience with machine learning data preparation concepts (cross validation, folding, boosting, feature engineering) with ...

We are looking for aMLOps Engineerto join our team and contribute to developing robust data solutionsto support our Machine Learning,Data Science, Data Engineering and Software Engineering. Position ...

... machine learning engineers to deploy models in production both in real-time and in batch process and systematically track model performance Assist engagement with key business stakeholders in ...

Senior ML Ops Engineer

Dallas, TX

$103.80K - $142.60K/yr

Machine Learning Algorithms. * c. Statistical Modeling. * d. End to end deployment. * e. Metric generation. * f. Model monitoring and deployment. * g. Prompt Engineering, 3. Hand on with ML Model ...

Engineer

Irving, TX · On-site

$95K - $105K/yr

Hands-on knowledge in machine learning frameworks like PyTorch, TensorFlow, Keras * Hands-On ... Prompt engineering * Deployment and maintenance of AI models across all environments including ...

Engineer

Irving, TX · On-site

$90K - $100K/yr

Hands-on knowledge in machine learning frameworks like PyTorch, TensorFlow, Keras * Hands-On ... Prompt engineering * Deployment and maintenance of AI models across all environments including ...

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Entry Level Machine Learning Engineer information

See Dallas, TX salary details

$29.7K

$68.6K

$116.7K

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

As of May 30, 2026, the average yearly pay for entry level machine learning engineer in Dallas, TX is $68,615.00, according to ZipRecruiter salary data. Most workers in this role earn between $50,900.00 and $77,700.00 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.
What are the most commonly searched types of Machine Learning Engineer jobs in Dallas, TX? The most popular types of Machine Learning Engineer jobs in Dallas, TX are:
What are popular job titles related to Entry Level Machine Learning Engineer jobs in Dallas, TX? For Entry Level Machine Learning Engineer jobs in Dallas, TX, the most frequently searched job titles are:
What job categories do people searching Entry Level Machine Learning Engineer jobs in Dallas, TX look for? The top searched job categories for Entry Level Machine Learning Engineer jobs in Dallas, TX are:
What cities near Dallas, TX are hiring for Entry Level Machine Learning Engineer jobs? Cities near Dallas, TX with the most Entry Level Machine Learning Engineer job openings:
Junior AI/ML Engineer (Data & Cloud Platforms)

Junior AI/ML Engineer (Data & Cloud Platforms)

Mod Op

Dallas, TX • On-site

$113.30K - $136K/yr

Full-time

Posted 25 days ago


Job description

About Mod Op
Mod Op is a full-service advertising agency able to offer clients a full suite of solutions. Mod Op can offer you access to low-cost, high-quality health care options and a team of enthusiastic, collaborative and motivated coworkers who see career development and personal development as intertwined.
At Mod Op, we're more than just an agency-we're a team of forward-thinking professionals who are passionate about driving client success. We believe in fostering meaningful relationships, collaborating across disciplines, and delivering impactful solutions that help businesses grow. If you are a strategic thinker with a passion for building lasting client partnerships, we'd love to hear from you. Join us and be part of a company that values innovation, creativity, and excellence in everything we do.
About the role
As a Junior AI/ML Engineer (Data & Cloud Platforms) with 1-2 years of experience, you will support the development of scalable data systems and contribute to AI and machine learning initiatives. This role combines data engineering, cloud technologies, and machine learning implementation to help build intelligent data-driven solutions.
You will work with AWS, GCP, and Azure cloud services, integrate with CRM and marketing platforms, and support analytics and AI solutions through tools such as Google Looker and Tableau. The role will involve working with both data pipelines and machine learning workflows to enable advanced analytics and automation.
The position operates under a hybrid work model, requiring in-office presence at the Dallas, Texas location two days per week, with the remaining days worked remotely.
What you'll do
Data Pipeline Development:
Assist in designing, developing, and maintaining scalable ETL/ELT pipelines across cloud platforms such as GCP, AWS, and Azure, using services like Dataflow, Cloud Composer (Airflow), Azure Synapse, and AWS Data Pipelines.
Data Integration:
Work with structured and unstructured data sources, including CRM systems, marketing platforms, APIs, and internal business systems, to support analytics and AI-driven applications.
Database Management:
Develop and optimize queries for SQL and NoSQL databases such as Teradata, BigQuery, Cassandra, and cloud data warehouses.
Machine Learning Implementation:
Support the development and deployment of machine learning models using Python and data science libraries (Pandas, NumPy, Scikit-learn) and cloud AI services such as GCP Vertex AI, AWS SageMaker, or Azure ML.
AI-Enabled Data Workflows:
Assist in building data pipelines that support predictive analytics, automation, and AI-driven insights.
Data Visualization:
Build and maintain dashboards using Google Looker and Tableau to help business and marketing teams understand and act on data insights.
Collaboration:
Work closely with data engineers, analysts, data scientists, and marketing teams to understand business requirements and support the development of data and AI solutions.
Required Qualifications
Cloud Platforms:
Hands-on experience with GCP, AWS, or Azure, particularly in data engineering or machine learning environments.
Programming Skills:
Strong proficiency in Python with experience using data processing and machine learning libraries such as Pandas, NumPy, and Scikit-learn.
Database Experience:
Experience working with SQL and NoSQL databases, including platforms such as BigQuery, Teradata, Cassandra, or similar technologies.
Data Visualization:
Experience building dashboards and reports using Google Looker or Tableau.
Machine Learning Knowledge:
Basic understanding of machine learning workflows, model training, evaluation, and deployment in cloud environments.
Data Automation & Transformation:
Experience with Alteryx or similar tools for workflow automation and data preparation.
Preferred Qualifications
Experience with data warehousing platforms such as Snowflake or Redshift.
Exposure to Apache Spark, Airflow, or other orchestration tools.
Familiarity with MLOps practices and cloud-based ML platforms.
Understanding of data governance, security, and compliance practices.
Relevant certifications such as Google Cloud Professional Data Engineer or Machine Learning certifications.
Mod Op, LLC provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.