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Machine Learning Engineer New Grad Jobs in Arlington, TX

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$28.3K

$115.9K

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How much do machine learning engineer new grad jobs pay per year?

As of Aug 11, 2026, the average yearly pay for machine learning engineer new grad in Arlington, TX is $115,885.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,300.00 and $139,500.00 per year, depending on experience, location, and employer.

What is a machine learning engineer new grad?

A Machine Learning Engineer New Grad job is an entry-level role for recent graduates specializing in machine learning and artificial intelligence. It typically involves developing, training, and deploying machine learning models, working with large datasets, and optimizing algorithms for performance. New grads in this role often collaborate with data scientists, software engineers, and product teams to integrate models into applications. Employers look for proficiency in programming (Python, TensorFlow, PyTorch), a strong foundation in ML concepts, and experience with data processing. This role provides an opportunity to gain hands-on industry experience and grow technical skills in real-world applications.

What are the key skills and qualifications needed to thrive in the machine learning engineer new grad position, and why are they important?

To thrive as a Machine Learning Engineer New Grad, a strong background in computer science, statistics, and mathematics, often supported by a relevant degree, is essential. Familiarity with programming languages like Python or Java, machine learning frameworks (such as TensorFlow or PyTorch), and basic knowledge of data tools and cloud platforms is typically required. Effective problem-solving, eagerness to learn, and clear communication help new grads excel when collaborating on projects and learning from senior team members. These skills and qualities are vital for adapting quickly, contributing to team goals, and building a successful foundation in this fast-evolving technical field.

What are the typical day-to-day tasks of a machine learning engineer new grad?

As a Machine Learning Engineer New Grad, your daily tasks often include collecting and preprocessing data, developing and testing machine learning models, and analyzing model performance. You may work closely with data scientists and software engineers to integrate models into production systems and address real-world business problems. Participating in team meetings, code reviews, and collaborative projects is common, providing opportunities to learn best practices and receive mentorship. This hands-on, varied workload helps you quickly build technical and collaborative skills early in your career.

What are popular job titles related to Machine Learning Engineer New Grad jobs in Arlington, TX? For Machine Learning Engineer New Grad jobs in Arlington, TX, the most frequently searched job titles are:
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What cities near Arlington, TX are hiring for Machine Learning Engineer New Grad jobs? Cities near Arlington, TX with the most Machine Learning Engineer New Grad job openings:
Machine Learning Engineer New Grad jobs near you
Infographic showing various Machine Learning Engineer New Grad job openings in Arlington, TX as of August 2026, with employment types broken down into 78% Full Time, 9% Part Time, and 13% Contract. Highlights an 84% In-person, and 16% Remote job distribution, with an average salary of $115,885 per year, or $55.7 per hour.

Compliance, Machine Learning Engineer, Dallas, Vice President

Goldman Sachs

Dallas, TX • On-site

Full-time

Re-posted 23 days ago

Goldman Sachs rating

8.3

Company rating: 8.3 out of 10

Based on 27 frontline employees who took The Breakroom Quiz

47th of 171 rated banks

Job description

Are you passionate about delivering mission-critical, high quality machine learning models, using cutting-edge technology, in a dynamic environment? 

OUR IMPACT

We are Compliance Engineering, a global team of more than 300 engineers and scientists who work on the most complex, mission-critical problems. 

We:

  • build and operate a suite of platforms and applications that prevent, detect, and mitigate regulatory and reputational risk across the firm. 
  • have access to the latest technology and to massive amounts of structured and unstructured data.
  • leverage modern frameworks to build responsive and intuitive UX/UI and Big Data applications.

Within Compliance engineering, we are hiring for a Machine Learning Engineering role within Models Engineering. The firm is making a significant investment improve the precision/ recall of the Compliance models portfolio in 2024. To achieve that we are hiring experienced MLEs who have experience of developing and deploying ML models for big data in a distributed architecture.

HOW YOU WILL FULFILL YOUR POTENTIAL

As a member of our team, you will:

  • Work with large scale structure and unstructured data. Drive end to end Machine Learning projects that have a high degree of scale and complexity
  • Build infra for machine learning which involves feature engineering and scaling models to work at scale
  • Develop, productionize, and maintain ml models
  • Run ML experiments by constantly tuning the features and the modeling approaches, documenting findings and results
  • Collaborate closely with ML researchers, to accelerate the usage of cutting edge models
  • Perform code reviews and ensure code quality

QUALIFICATIONS

A successful candidate will possess the following attributes:

  • A Bachelor's or Master's degree in Computer Science, or a similar field of study.
  • 10+ years of hands-on experience with building scalable machine learning systems 
  • Solid coding skills and strong Computer Science fundamentals (algorithms, data structures, software design)
  • Expertise in Python & PySpark
  • Experience in working with distributed technologies like Scala, Pyspark, Iceberg, HDFS file formats (avro, parquet), AWS/ GCP,  big data feature engineering.
  • Experience in system design and evaluating the pros and cons of database choices, schema definition for data storage.
  • Extensive experience with Machine Learning and Deep Learning toolkits (Tensorflow, PyTorch, Scikit-Learn, HuggingFace)

Experience in some of the following is desired and can set you apart from other candidates : 

  • Prior experience with LLMs and Prompt Engineering
  • Prior experience in architecting/ deploying ML applications on AWS/ GCP
  • Prior experience in code reviews/ architecture design for distributed systems. 
ABOUT GOLDMAN SACHS

 
At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. 

 
We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers. 

 
We're committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: https://www.goldmansachs.com/careers/footer/disability-statement.html

 

 
The Goldman Sachs Group, Inc., 2023. All rights reserved.
Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.

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About Goldman Sachs

Sourced by ZipRecruiter

At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1869

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