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Scientific Machine Learning Jobs in Rhode Island

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Collaborate closely with product managers, data scientists, and backend engineers to deeply ...

Quora

$139K - $168K/yr

D. in Computer Science, Engineering or a related technical field * Strong understanding of mathematical foundations of Machine Learning algorithms * Experience of transformer models and LLM ...

Quora

$139K - $168K/yr

D. in Computer Science, Engineering or a related technical field * Strong understanding of mathematical foundations of Machine Learning algorithms * Experience of transformer models and LLM ...

Quora

$139K - $168K/yr

D. in Computer Science, Engineering or a related technical field * Strong understanding of mathematical foundations of Machine Learning algorithms * Experience of transformer models and LLM ...

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All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in Rhode Island

Scientific Machine Learning information

What is scientific machine learning?

Scientific machine learning (SciML) is an interdisciplinary field that combines principles from machine learning and scientific computing to solve complex scientific and engineering problems. It involves developing algorithms and models that can learn from data and physical laws, such as differential equations, to make predictions, optimize systems, or gain insights into phenomena. SciML is widely used in areas like physics, biology, climate science, and engineering, enabling researchers to accelerate simulations and make data-driven discoveries. The field often leverages both traditional numerical methods and modern machine learning techniques, making it a rapidly evolving area of research.

What are some common challenges faced by professionals in Scientific Machine Learning, and how can they be addressed?

Professionals in Scientific Machine Learning often encounter challenges such as integrating domain-specific scientific knowledge with machine learning models, managing large and complex datasets, and ensuring that models are interpretable and physically consistent. Collaboration with domain experts and interdisciplinary teams is essential to bridge knowledge gaps and validate results. To address these challenges, it is helpful to invest time in understanding the underlying scientific principles, keep up-to-date with advancements in both machine learning and scientific fields, and utilize specialized tools and frameworks designed for scientific data.

What are the key skills and qualifications needed to thrive as a Scientific Machine Learning professional, and why are they important?

To thrive as a Scientific Machine Learning professional, you need a strong background in mathematics, statistics, programming (often Python), and domain-specific scientific knowledge, typically with a graduate degree in a STEM field. Proficiency in machine learning frameworks (such as TensorFlow or PyTorch), scientific computing tools (like NumPy, SciPy), and experience with high-performance computing are commonly required. Critical thinking, problem-solving, and collaborative communication are vital soft skills for designing experiments and interpreting complex data. These skills ensure robust, reproducible results and the ability to bridge scientific inquiry with advanced computational methods.

What is the difference between Scientific Machine Learning vs Data Scientist?

AspectScientific Machine LearningData Scientist
Required credentialsAdvanced degrees in CS, ML, or related fields; knowledge of scientific computingDegree in CS, statistics, or related fields; strong analytical skills
Work environmentResearch labs, academia, industry R&D teamsBusiness analytics, tech companies, consulting firms
Industry usageResearch, scientific computing, engineering simulationsBusiness insights, predictive modeling, data analysis

Scientific Machine Learning focuses on integrating scientific knowledge with machine learning techniques for research and engineering applications. Data Scientists analyze data to extract insights and build predictive models for business or operational purposes. While both roles require strong technical skills, Scientific Machine Learning emphasizes scientific computing and domain-specific modeling, whereas Data Scientists focus on data analysis and visualization.

What are popular job titles related to Scientific Machine Learning jobs in Rhode Island? For Scientific Machine Learning jobs in Rhode Island, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in Rhode Island look for? The top searched job categories for Scientific Machine Learning jobs in Rhode Island are:
Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Rhode Island as of July 2026, with employment types broken down into 1% As Needed, 71% Full Time, 25% Part Time, 1% Temporary, and 2% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution.
Director Artificial Intelligence and Machine Learning (59360)

Director Artificial Intelligence and Machine Learning (59360)

AAA Northeast

Providence, RI • On-site, Remote

$6.0K/mo

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 9 days ago

AAA Northeast rating

7.8

Company rating: 7.8 out of 10

Based on 35 frontline employees who took The Breakroom Quiz

174th of 299 rated insurance

Job description


What You Will Do:

  • Develop and communicate the enterprise AI vision, establishing a multi-year technical strategy that advances innovation, scalability, and competitive differentiation.
  • Build, mentor, and lead high-performing cross-functional AI/Machine Learning teams, fostering technical excellence, collaboration, and a culture of continuous learning.
  • Own the AI roadmap and investment portfolio, prioritizing initiatives that balance near-term business impact with long-term innovation goals.
  • Drive frontier research in machine learning, deep learning, and generative AI, identifying emerging capabilities and translating them into strategic advantage.
  • Lead rapid prototyping of novel algorithms, model architectures, and experimentation frameworks to accelerate discovery and validate new opportunities.
  • Align AI initiatives with enterprise priorities, partnering with senior stakeholders to define use cases, success metrics, and measurable ROI targets.
  • Translate research breakthroughs into scalable, production-ready solutions by guiding model development, deployment, and operationalization across the organization.
  • Serve as a thought leader for the organization by representing the company in industry conferences, strategic partnerships, and external publications.

What You Will Need

  • Master's Degree Computer Science, AI/ML, or related field required
  • PhD Computer Science, AI/ML, or related field preferred
  • 10+ years AI and Machine Learning  required 
  • 5+ years Leadership roles  required 
  • 3+ years Experience managing teams of data scientists and engineers  required 
  • Certifications in cloud platforms (AWS, Azure, or Google Cloud)  preferred
  • Certifications in AI, machine learning, or data science  preferred

Why AAA Northeast

Career Growth: With ongoing world-class training and proven career paths, you'll have the opportunity to develop expertise and advance your career within AAA Northeast. 
Trusted Legacy: With over 120 years of service excellence, we have a long track record of protecting our members as well as our employees and their families. 
Future-Focused: With new business offerings and increasing digital presence, we are focused on innovating for the future to sustain our success. 

What We Offer

  • Award-Winning: We’ve been named as a Top Employer for the last 7 years 
  • Health Coverage: Medical coverage with employer contributions covering up to 93% of the premium cost, plus dental and vision options. 
  • Retirement: 6% company match on 401(k) retirement plan contribution, with contributions fully vested and made every pay period 
  • Paid Time off: 3 weeks’ vacation, 12 holidays, 8 sick days, 48 hours of volunteer time annually 
  • Additional Perks: Free AAA membership, insurance discounts, travel commission refund, up to $625 in Wellness Incentives, up to $6k in tuition reimbursement, and more! 
  • Compensation: Competitive base pay, annual bonus opportunities, and for certain roles, additional monthly and/or quarterly incentive compensation. The posted salary range represents the full range grade for this role, with individual pay based on job-related skills, experience, shift, and geographic location.

At AAA Northeast, how we work together matters. We are a highly collaborative organization that values connection, transparency, and trust. Our “cameras on” approach during virtual meetings reflects our expectation that team members are present, engaged and actively participating, helping to build strong working relationships and a sense of shared accountability, no matter where we’re located. 
We are also proud of our diverse culture, shaped by the talents, experiences, and perspectives of our employees. AAA Northeast is an equal opportunity employer and is committed to fair and equitable practices in recruiting, hiring, and advancement. We do not discriminate based on race, color, creed or religion, national origin, sex, age, sexual orientation, veteran status, gender identity or expression, disability, genetic information, marital status, pregnancy, or membership in any other protected class. We thrive when our team members bring their whole selves to work.

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