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Machine Learning Quantum Computing Jobs in Homestead, PA

ARMADA

Data Engineer

Wexford, PA · On-site

$108K - $130K/yr

... cloud computing and data processing. In this pivotal role, you will collaborate with cross ... Solid understanding of machine learning models, tools, libraries, and approaches. * Experience with ...

Varsity Tutors

Python Tutor

Pittsburgh, PA · Remote

$18 - $40/hr

Emphasizes readable, maintainable code and connects Python to machine learning, web scraping, scientific computing, and DevOps applications. * Curriculum Awareness & Adaptive Instruction: Familiar ...

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All JobsMachine Learning Quantum Computing JobsMachine Learning Quantum Computing Jobs in Homestead, PA

Machine Learning Quantum Computing information

See Homestead, PA salary details

$23.2K

$38.7K

$79.9K

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

As of Jul 11, 2026, the average yearly pay for machine learning quantum computing in Homestead, PA is $38,675.00, according to ZipRecruiter salary data. Most workers in this role earn between $29,500.00 and $41,800.00 per year, depending on experience, location, and employer.

What is the difference between Machine Learning Quantum Computing vs Data Scientist?

AspectMachine Learning Quantum ComputingData Scientist
Required CredentialsAdvanced degrees in quantum computing, machine learning, or related fieldsDegree in data science, statistics, or computer science
Work EnvironmentResearch labs, tech companies focusing on quantum tech, academiaBusiness environments, tech companies, consulting firms
Industry UsageEmerging quantum tech industry, research institutionsFinance, healthcare, marketing, e-commerce
Common Search/ComparisonQuantum algorithms, quantum machine learningData analysis, predictive modeling

Machine Learning Quantum Computing specialists focus on developing algorithms that leverage quantum mechanics to enhance machine learning tasks, often requiring advanced knowledge of quantum physics. Data Scientists analyze and interpret large datasets using traditional machine learning techniques. While both roles involve machine learning, the former emphasizes quantum computing applications, whereas the latter centers on data analysis in conventional computing environments.

What are the key skills and qualifications needed to thrive as a Machine Learning Quantum Computing Specialist, and why are they important?

To thrive in Machine Learning Quantum Computing, you need strong foundations in quantum mechanics, linear algebra, and advanced machine learning concepts, typically supported by a degree in physics, computer science, or a related field. Familiarity with quantum programming languages (such as Qiskit or Cirq), cloud-based quantum platforms, and proficiency in Python are usually required, alongside experience with relevant certifications or coursework. Strong problem-solving skills, adaptability, and effective collaboration are vital soft skills in this interdisciplinary field. These competencies are crucial for driving innovation and bridging the gap between quantum computing and practical machine learning applications.

How do professionals in Machine Learning Quantum Computing typically collaborate with interdisciplinary teams?

Professionals in Machine Learning Quantum Computing often work closely with experts in physics, computer science, and engineering. Collaboration usually involves translating quantum concepts for machine learning specialists and vice versa, ensuring that algorithms are both theoretically sound and practically implementable on quantum hardware. Regular meetings, code reviews, and knowledge-sharing sessions are standard, as interdisciplinary insight is crucial for advancing research and developing scalable solutions. Effective communication and a willingness to learn from other domains are essential for success in these teams.

What is Machine Learning Quantum Computing?

Machine Learning Quantum Computing is an interdisciplinary field that combines principles of quantum computing with machine learning techniques. It aims to leverage the computational power of quantum computers to enhance the performance of machine learning algorithms, potentially solving complex problems more efficiently than classical computers. This area includes developing quantum algorithms for tasks such as classification, clustering, and optimization, as well as using machine learning to improve quantum hardware and error correction. Researchers expect that, as quantum hardware matures, this field could revolutionize data analysis, cryptography, and scientific discovery.
What cities near Homestead, PA are hiring for Machine Learning Quantum Computing jobs? Cities near Homestead, PA with the most Machine Learning Quantum Computing job openings:
Machine Learning Quantum Computing jobs near you

Research Engineer, Learnable Planner (Integration)

Waabi

Pittsburgh, PA • On-site, Remote

$159K - $296K/yr

Full-time

Posted 25 days ago

Job description

Waabi, founded by AI visionary Raquel Urtasun, is the leader in Physical AI. With a world-class team, we're unlocking the next era of autonomous transportation with technology that's powering commercial autonomous trucks and robotaxis. Waabi is backed by and partners with world leaders in AI, automotive, logistics, and deep tech.

With offices in Toronto, San Francisco, Dallas, and Pittsburgh, Waabi is growing quickly and looking for diverse, innovative and collaborative candidates who want to impact the world in a positive way. To learn more visit: www.waabi.ai

The Motion Planning team delivers the core module within the autonomy stack that makes decisions and generates trajectories for our self-driving trucks. As a research engineer for Learnable Planner you will support integration of new AI technologies into our autonomy/planner stack enabling our launch of fully driverless autonomous trucks. You will contribute towards Waabi's vision of a single AI system that learns end-to-end and in a provably safe manner as well as our revolutionary high-fidelity, closed-loop simulator, Waabi World.
 
You will...
- Integrate cutting-edge ML models in production planning stack from development to validation, deployment, and monitoring
- Develop necessary interfaces and pipelines in simulation for testing prototype or production planning models
- Work closely with motion planning sub-teams and research scientists to improve our planner architecture and develop rich and novel representations that can facilitate end-to-end solutions
- Champion engineering excellence, ensuring high-quality, well structured and tested code.
- Stay up-to-date with the latest advancements in the field of artificial intelligence, machine learning, computer vision, and self-driving technologies, and apply insights from the literature.
- Work with large datasets from various sources as well as Waabi World, our high-fidelity simulator.
- Contribute to the publication of research findings in conferences as well as Waabi's blog.
 
Qualifications:
- MS/PhD in machine learning, computer science, engineering, or a related field. Exceptional Bachelor’s students will also be considered.
- Experience in ML-based or classical techniques for planning/decision making (e.g., imitation and reinforcement learning, optimization-based approaches, search methods, probabilistic reasoning).
- Passion for taking research ideas and turning them into practical solutions for real-world applications.
- Open-minded and collaborative team player with willingness to help others.
- Solid understanding of computing fundamentals, including code efficiency.
- Experience in deep learning frameworks such as PyTorch.
- Proficiency in Python, Rust, C++ and/or CUDA.
 
Bonus/nice to have:
- Experience deploying ML/DL models to a production motion planning or related robotics stack.
- Experience in iterating on a model including evaluation, introspection and fine-tuning.
- Strong grasp of machine learning literature, including current trends and state-of-the-art techniques.
- Comfortable with model compilation and exporting, lower level concepts like TensorRT, CUDA kernels.
The US yearly salary range for this role is: $159,000 - $296,000 USD in addition to competitive perks & benefits. Waabi US Inc.’s yearly salary ranges are determined based on several factors in accordance with the Company’s compensation practices. The salary base range is reflective of the minimum and maximum target for new hire salaries for the position across all US locations.  Note: The Company provides additional compensation for employees in this role, including equity incentive awards and an annual performance bonus.

Perks/Benefits:
- Competitive compensation and equity awards.
- Health and Wellness benefits encompassing Medical, Dental and Vision coverage (for full-time employees only).
- Unlimited Vacation.
- Flexible hours and Work from Home support.
- Daily drinks, snacks and catered meals (when in office).
- Regularly scheduled team building activities and social events both on-site, off-site & virtually.
- As we grow, this list continues to evolve! 

Waabi is a technology start-up building technologies to transform the way the world moves. Join our talented team to be a part of the future and to make an impact!

Waabi is an equal opportunity employer. We celebrate diversity and are committed to creating a supportive, inclusive, and accessible workplace for all our employees. We seek applicants of all backgrounds and identities, across race, color, ethnicity, national origin or ancestry, age, citizenship, religion, sex, sexual orientation, gender identity or expression, military or veteran status, marital status, pregnancy or parental status, caregiver status, disability, or any other characteristic protected by law. We make workplace accommodations for qualified individuals with disabilities as required by applicable law. If reasonable accommodation is needed to participate in the job application or interview process please let our recruiting team know.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.