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Quantum Machine Learning Engineer Jobs in Utah (NOW HIRING)

They are seeking a highly skilled Machine Learning Engineer to manage large datasets, optimize cloud-based computing resources, and train advanced machine-learning models to contribute to new ...

Senior Machine Learning Engineer

Lehi, UT ยท On-site +1

$144K - $233K/yr

Following the launch of Forge , Entrata's proprietary AI platform, we are looking for a Senior Machine Learning Engineer to drive the next generation of our applied AI capabilities. You will play a ...

Senior Machine Learning Engineer

Lehi, UT ยท On-site +1

$144K - $233K/yr

Following the launch of Forge , Entrata's proprietary AI platform, we are looking for a Senior Machine Learning Engineer to drive the next generation of our applied AI capabilities. You will play a ...

Senior Machine Learning Engineer

Lehi, UT ยท On-site

$144K - $233K/yr

We are seeking a Senior Machine Learning Engineer to help build and scale Entrata's applied AI capabilities. This role will focus on adapting and fine-tuning foundation models for property management ...

The Opportunity Adobe is looking for Machine Learning Engineer interns to work on some of the most impactful AI systems in the industry - from generative AI features and intelligent agents to search ...

* 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 ...

* 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 ...

* 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 ...

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Quantum Machine Learning Engineer information

See Utah salary details

$28.7K

$117.2K

$176.2K

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

As of Sep 14, 2026, the average yearly pay for quantum machine learning engineer in Utah is $117,228.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,400.00 and $141,100.00 per year, depending on experience, location, and employer.

What is a quantum machine learning engineer?

A Quantum Machine Learning Engineer is a professional who combines expertise in quantum computing and machine learning to develop algorithms and solutions that leverage quantum hardware for advanced data processing tasks. They work on designing, implementing, and testing quantum algorithms that can solve problems faster or more efficiently than classical computers. Their work often involves collaborating with physicists, data scientists, and software engineers to bridge the gap between quantum theory and practical applications. This role requires strong backgrounds in quantum mechanics, computer science, and statistical learning techniques.

What are the key skills and qualifications needed to thrive as a quantum machine learning engineer?

To thrive as a Quantum Machine Learning Engineer, you need a strong background in quantum computing, machine learning, linear algebra, and programming (often Python or C++), typically supported by an advanced degree in physics, computer science, or a related field. Familiarity with platforms like Qiskit, Cirq, or TensorFlow Quantum, and knowledge of quantum algorithms and cloud-based quantum computing services are essential. Creative problem-solving, analytical thinking, and strong collaboration skills help distinguish top performers in this interdisciplinary field. Mastery of these skills enables innovation in developing and deploying quantum machine learning solutions to solve complex, cutting-edge problems.

How do quantum machine learning engineers typically collaborate with classical machine learning teams and quantum hardware specialists?

Quantum Machine Learning Engineers often serve as a bridge between classical machine learning experts and quantum hardware specialists. They work closely with data scientists to adapt machine learning algorithms for quantum environments and collaborate with hardware teams to ensure algorithms are optimized for specific quantum processors. Regular cross-functional meetings, code reviews, and joint problem-solving sessions are common, fostering a highly collaborative work environment. This collaboration is essential for successfully integrating quantum solutions into existing workflows and advancing the organization's quantum computing initiatives.

Is quantum machine learning a good career?

Quantum machine learning engineers work at the intersection of quantum computing and machine learning, focusing on developing algorithms that leverage quantum hardware. The field is emerging with high growth potential, requiring skills in quantum algorithms, programming languages like Python, and understanding of both quantum mechanics and machine learning principles. As quantum technology advances, demand for specialists in this area is expected to increase, making it a promising career path for those with relevant expertise.

What are popular job titles related to Quantum Machine Learning Engineer jobs in Utah?

For Quantum Machine Learning Engineer jobs in Utah, the most frequently searched job titles are:

What job categories do people searching Quantum Machine Learning Engineer jobs in Utah look for?

The top searched job categories for Quantum Machine Learning Engineer jobs in Utah are:

What cities in Utah are hiring for Quantum Machine Learning Engineer jobs?

Cities in Utah with the most Quantum Machine Learning Engineer job openings:

Machine Learning Engineer

Salt Lake City, UT โ€ข On-site

Full-time

Re-posted 9 days ago


Job description

Job Summary:
Leash Biosciences is at the forefront of integrating machine learning with drug discovery, aiming to revolutionize medicinal chemistry. They are seeking a highly skilled Machine Learning Engineer to manage large datasets, optimize cloud-based computing resources, and train advanced machine-learning models to contribute to new therapies for devastating diseases.
Responsibilities:
โ€ข Manage and optimize data processing workflows for large-scale datasets, with an approach akin to language data handling.
โ€ข Scale and maintain machine learning model training processes, with a focus on cloud environments (primarily Google Cloud, with flexibility to other platforms).
โ€ข Collaborate closely with ML researchers, data scientists, and lab automation teams to ensure seamless integration of lab data and ML model training.
โ€ข Innovate and iterate on our existing technology stack, taking the initiative to solve problems and improve our ML operations.
โ€ข Act as a self-sufficient project manager, overseeing your projects from conception to completion.
Qualifications:
Required:
โ€ข Strong experience in machine learning engineering, including data handling, model training, and scaling in cloud environments.
โ€ข Comfortable building ML infrastructure
โ€ข Experience working with large amounts of text data, NLP, or training LLMs
โ€ข Demonstrated capability to make informed decisions, take ownership of solutions, and drive projects forward in a startup environment.
โ€ข Excellent collaboration skills, with the ability to work effectively with cross-functional teams.
Preferred:
โ€ข Familiarity with common MLops tooling (e.g., Dagster, Prefect, Airflow, Docker, MLflow, Kubeflow, W&B, Ray, etc.)
โ€ข Ability to manage own compute cluster
โ€ข Ability to maximize GPU utilization and keep cluster busy 24/7
โ€ข Ability to analyze model results and kick off new experiments in response
โ€ข Experience with BERT or similar language models in PyTorch.
โ€ข Experience or interest in biology, chemistry, or related fields is a plus.
Company:
Leash Bio uses AI and machine learning to innovate drug design and medicinal chemistry. Founded in 2021, the company is headquartered in Salt Lake City, USA, with a team of 2-10 employees. The company is currently Early Stage.