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Machine Learning Engineer New Grad Jobs in Salt Lake City, UT

* Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch * Build and maintain the infrastructure around RL training: rollout collection ...

Senior Engineer - Machine Learning

Midvale, UT ยท Hybrid

$98K - $135K/yr

As a Senior Engineer, Machine Learning at Berkadia, you'll be at the forefront of applying cutting-edge machine learning and generative AI to redefine how the commercial real estate industry operates.

As a Senior Engineer, Machine Learning at Berkadia, you'll be at the forefront of applying cutting-edge machine learning and generative AI to redefine how the commercial real estate industry operates.

Showing results 21-40

Machine Learning Engineer New Grad information

See Salt Lake City, UT salary details

$30.5K

$124.6K

$187.3K

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

As of Sep 3, 2026, the average yearly pay for machine learning engineer new grad in Salt Lake City, UT is $124,611.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,200.00 and $150,000.00 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 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 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 popular job titles related to Machine Learning Engineer New Grad jobs in Salt Lake City, UT?

For Machine Learning Engineer New Grad jobs in Salt Lake City, UT, the most frequently searched job titles are:

What cities near Salt Lake City, UT are hiring for Machine Learning Engineer New Grad jobs?

Cities near Salt Lake City, UT with the most Machine Learning Engineer New Grad job openings:

Machine Learning Engineer

Bespoke Labs

Salt Lake City, UT โ€ข On-site

Full-time

Re-posted 17 days ago


Job description

  • Own model training and post-training pipelines end to end: SFT, RLHF, PPO, DPO, and reward model training in PyTorch

  • Build and maintain the infrastructure around RL training: rollout collection, data curation, reward model serving, and experiment orchestration

  • Run and scale training experiments on cloud or HPC (AWS, GCP, SLURM, Ray), and debug throughput, stability, and convergence issues

  • Build evaluation harnesses and benchmark infrastructure, with held-out sets and contamination controls, so results are trustworthy

  • Read eval signal and training curves to determine whether a change actually helped, and feed findings back to the research and environment teams

  • Integrate RL environments into the training stack, working with environment authors on interfaces, reward plumbing, and agent loop mechanics

  • Implement methods from recent ML papers quickly and turn them into production-grade systems