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Quantum Machine Learning Engineer Jobs in Saint Joseph, MI

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Welder I

South Haven, MI · On-site

$19 - $25/hr

Responsible for the equipment care and proper machine settings to optimize the welding equipment ... Utilizing engineering drawings which display proper assembly and dimensional characteristics to ...

Griffin Tool Inc.

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CNC Programmer

Stevensville, MI · On-site

$55K - $70K/yr

Operate CNC machines * Use hand tools; grinders; saws; routers; sanders * Successful history of ... learning, and looking for growth within the company. We offer a full benefits package to all ...

All JobsQuantum Machine Learning Engineer JobsQuantum Machine Learning Engineer Jobs in Saint Joseph, MI

Quantum Machine Learning Engineer information

See Saint Joseph, MI salary details

$29.7K

$121.6K

$182.7K

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

As of Aug 6, 2026, the average yearly pay for quantum machine learning engineer in Saint Joseph, MI is $121,569.00, according to ZipRecruiter salary data. Most workers in this role earn between $95,800.00 and $146,300.00 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.

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.

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.
What cities near Saint Joseph, MI are hiring for Quantum Machine Learning Engineer jobs? Cities near Saint Joseph, MI with the most Quantum Machine Learning Engineer job openings:
Quantum Machine Learning Engineer jobs near you

Machine Learning Engineer

Bespoke Labs

Berrien Springs, MI

Full-time

Re-posted 20 days ago

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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