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Quantum Machine Learning Engineer Jobs in Maryland

Bespoke Labs

Machine Learning Engineer

Annapolis, MD · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Xometry

Staff Machine Learning Engineer

North Bethesda, MD · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We are looking for a Staff Machine Learning Engineer to join our growing AI/ML team. This is a senior individual contributor role with broad technical scope and meaningful organizational impact. You ...

Xometry

Staff Machine Learning Engineer

North Bethesda, MD · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

We are looking for a Staff Machine Learning Engineer to join our growing AI/ML team. This is a senior individual contributor role with broad technical scope and meaningful organizational impact. You ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

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Showing results 21-40

All JobsQuantum Machine Learning Engineer JobsQuantum Machine Learning Engineer Jobs in Maryland

Quantum Machine Learning Engineer information

See Maryland salary details

$30.6K

$125K

$187.8K

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

As of Aug 18, 2026, the average yearly pay for quantum machine learning engineer in Maryland is $124,976.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $150,400.00 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 Maryland?

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

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

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

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

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

Quantum Machine Learning Engineer jobs near you
Infographic showing various Quantum Machine Learning Engineer job openings in Maryland as of August 2026, with employment types broken down into 100% Full Time. Highlights an 66% In-person, and 34% Remote job distribution, with an average salary of $124,976 per year, or $60.1 per hour.

Machine Learning Engineer

Bespoke Labs

Annapolis, MD • On-site

Full-time

Re-posted yesterday

Job description

About Us

We are AI researchers and builders who understand how to curate data and RL environments that truly improve models. We curated OpenThoughts, one of the best open reasoning datasets, and have trained SOTA models such as Bespoke-MiniCheck and Bespoke-MiniChart.

We are embarked on a journey to build Environments that are entire digital worlds that can be used to push the frontier of agents.

What You'll Be Working On

You will work directly with our research team on RL environment and task creation for agent training. This means designing observation spaces, action spaces, reward signals, and success criteria for new environments — and building the infrastructure that makes world-scale RL training possible. This is a high-ownership role; you will be building novel systems, not maintaining legacy ones.

Must-Have Skills

3+ years of ML engineering experience — model training, fine-tuning, or post-training pipelines in research or production

Strong Python and deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed precision)

Hands-on experience with LLM post-training — SFT, RLHF, PPO, DPO, or reward model training — and understanding of how training data quality affects model behavior

Familiarity with RL frameworks (Gymnasium, dm_env) and the ability to design or modify reward functions for agent training objectives

Experience running experiments at scale on cloud or HPC (AWS, GCP, SLURM, or Ray)

Solid understanding of evaluation methodology — held-out sets, benchmark design, avoiding train/eval contamination

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