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Quantum Machine Learning Engineer Jobs in Delaware

Athena LLC

Role Overview The AI Engineer Intern will develop and enhance Large Language Models (LLMs) to ... Solid understanding of machine learning fundamentals and algorithms (classification, NLP, Deep ...

Tata Consultancy Service Limited

GenAI Engineer

Wilmington, DE · On-site

$100K - $110K/yr

Machine Learning, Deep Learning, LLMs, Prompt Engineering, Fine-tuning • Frameworks: TensorFlow, PyTorch • GenAI Tools: LangChain, LlamaIndex • Vector DB: Pinecone, FAISS • Cloud Technologies:

Sallie Mae

Senior Manager, Statistical Modeling

Newark, DE · On-site

$85K - $104K/yr

Oversee the full model development and machine learning lifecycle: data collection, preprocessing, feature engineering, model development, deployment, and monitoring. * Collaborate with cross ...

JP Morgan Chase

Lead Software Engineer

Wilmington, DE · On-site

As a Lead Software Engineer at JPMorgan Chase within the Corporate Technology, you are an integral ... Design and implement enterprise-grade Machine Learning platforms capable of deploying and running ...

J.P. Morgan

Lead Software Engineer

Wilmington, DE

As a Lead Software Engineer at JPMorgan Chase within the Corporate Technology, you are an integral ... Design and implement enterprise-grade Machine Learning platforms capable of deploying and running ...

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All JobsQuantum Machine Learning Engineer JobsQuantum Machine Learning Engineer Jobs in Delaware

Quantum Machine Learning Engineer information

See Delaware salary details

$31.5K

$128.9K

$193.7K

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

As of Jul 12, 2026, the average yearly pay for quantum machine learning engineer in Delaware is $128,880.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,600.00 and $155,100.00 per year, depending on experience, location, and employer.

What is the salary of quantum machine learning engineer?

The salary of a quantum machine learning engineer typically ranges from $100,000 to $150,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in quantum algorithms and programming languages like Python or Qiskit may offer higher compensation. Many positions also include benefits such as research opportunities and access to advanced quantum computing tools.

What engineers make $500,000?

Senior engineers in specialized fields such as software engineering, data engineering, or engineering management can earn $500,000 or more annually, especially with extensive experience, advanced skills, and in high-demand industries like technology or finance. Compensation often includes base salary, bonuses, and stock options, particularly at large tech companies or startups with significant growth potential.

Is quantum machine learning a good career?

Quantum machine learning engineers work at the intersection of quantum computing and machine learning, developing algorithms that leverage quantum hardware. The field is emerging, with high demand for specialized skills in quantum algorithms, programming languages like Qiskit, and understanding of both quantum physics and data science. Careers in this area can be rewarding but often require advanced education and continuous learning due to rapid technological advancements.

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.

Will MLE be replaced by AI?

Quantum Machine Learning Engineers work at the intersection of quantum computing and machine learning, developing algorithms that leverage quantum systems. While AI continues to advance, quantum computing is expected to complement classical machine learning rather than replace it entirely, and MLE roles will evolve to incorporate new quantum techniques and tools. Continuous learning in both quantum algorithms and machine learning is essential for professionals in this field.

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, and why are they important?

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 are popular job titles related to Quantum Machine Learning Engineer jobs in Delaware? For Quantum Machine Learning Engineer jobs in Delaware, the most frequently searched job titles are:
What job categories do people searching Quantum Machine Learning Engineer jobs in Delaware look for? The top searched job categories for Quantum Machine Learning Engineer jobs in Delaware are:
What cities in Delaware are hiring for Quantum Machine Learning Engineer jobs? Cities in Delaware with the most Quantum Machine Learning Engineer job openings:
Quantum Machine Learning Engineer jobs near you

AI Engineering Intern

Athena LLC

On-site, Remote

Full-time

Re-posted 5 days ago

Job description

At Athena, we empower possibility through transformative delegation. Our mission is to build the world's premier delegation platform, combining the strengths of exceptional Executive Assistants with advanced AI technologies to save our clients millions of hours each year.
Role Overview
The AI Engineer Intern will develop and enhance Large Language Models (LLMs) to improve task delegation workflows, instruction generation, and automate agentic processes. This role will also contribute to building and improving AI agentic systems that can reason through tasks, use tools, and support more reliable task execution across Athena workflows. You will play a crucial role in prototyping, developing, and deploying cutting-edge AI features that directly impact client productivity and efficiency.
Responsibilities
  • Assist in developing and fine-tuning large language models (LLMs) to better understand and generate instructions for complex tasks. You'll experiment with model parameters and training data to improve performance.
  • Build and integrate AI-driven features that improve task delegation workflows - for example, creating intelligent agents that break down client requests into actionable steps for our team.
  • Collaborate with senior AI engineers to prototype systems that use AI for agentic workflows, enabling the platform to automatically handle or delegate routine instructions.
  • Support the development of AI agentic components such as task planning, tool use, memory, prompt workflows, and orchestration logic to help agents operate more effectively in real-world scenarios.
  • Evaluate model outputs for accuracy and usefulness. Develop tests and metrics to assess how well the AI-generated instructions or recommendations are performing in real-world scenarios.
  • Help build lightweight evaluation harnesses and experiments to test agent behavior, workflow reliability, and the quality of AI-generated task execution.
  • Work cross-functionally with product and software engineers to implement AI solutions into the Athena platform. Communicate technical findings and iterate on solutions based on user feedback.

Qualifications
  • Currently pursuing (or recently completed) a degree in Computer Science, Stats, or related field, with coursework in machine learning or artificial intelligence.
  • Strong programming abilities in Python (and familiarity with ML libraries like TensorFlow, PyTorch). Comfortable with data structures, algorithms, and writing clean, efficient code.
  • Solid understanding of machine learning fundamentals and algorithms (classification, NLP, Deep Learning). Familiarity with concepts of training, fine-tuning, and evaluating models.
  • Knowledge of natural language processing techniques. Understanding how large language models work and experience using or implementing NLP models.
  • Interest in AI agentic systems, including areas such as prompt design, tool use, workflow orchestration, multi-step reasoning, or evaluation of LLM-based systems.
  • Ability to break down complex problems and experiment with creative AI solutions. Eagerness to learn new technologies and frameworks quickly.

Preferred Qualifications
  • Previous projects or internship experience involving machine learning or AI (especially work with LLMs or NLP projects).
  • Experience with ML ops or model deployment (e.g. using cloud AI services, Docker, REST APIs for model serving).
  • Familiarity with concepts like reinforcement learning, prompt engineering for LLMs, or building multi-agent systems.
  • Experience with data preprocessing pipelines, and working with datasets relevant to language models or automation tasks.
  • Exposure to agent evaluation, prompt pipelines, orchestration frameworks, or AI systems that interact with external tools or APIs is a plus.
  • Awareness of the latest trends and research in AI/ML (new model architectures, papers, etc.), showing a passion for staying up-to-date in the field.

Benefits
  • You will be mentored by Athena's AI and software engineering experts. They will provide guidance, code reviews, and support as you work on challenging AI projects, ensuring you learn best practices in the field.
  • Expect to engage with cutting-edge AI technology. You'll contribute to pioneering projects (like improving AI-driven delegation) that could become core Athena offerings, giving you tangible achievements to highlight in your career.
  • Be part of a collaborative, forward-thinking team. Interns at Athena are included in all aspects of company life - from daily stand-ups to social outings - receiving the same respect and perks as full-timers.
  • This internship will enhance your practical AI skills and professional network. You'll leave with a deeper understanding of how AI can automate and improve real-world processes, and you may earn opportunities for future employment at Athena.com based on your performance.

Apply