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Scientific Machine Learning Jobs in Alabama (NOW HIRING)

Varsity Tutors

Machine Learning Tutor

Tuscaloosa, AL · Remote

$40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Birmingham, AL · Remote

$40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Huntsville, AL · Remote

$40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Montgomery, AL · Remote

$40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Indeed

Machine Learning Engineer III

Huntsville, AL

Requires a Bachelor's degree in Computer Science, Mathematics, or Statistics, and a minimum of 8 ... Prior success in deploying impactful Machine Learning solutions to large-scale production systems ...

Indeed

Machine Learning Engineer

Huntsville, AL

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain ... You collaborate with engineers, data scientists, and product teams to define problems, test ...

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Scientific Machine Learning information

Is ML a high paying job?

Scientific Machine Learning roles typically offer high salaries due to the specialized skills required, such as expertise in deep learning, data analysis, and programming with tools like Python and TensorFlow. Compensation varies by industry, experience, and location but generally exceeds average tech salaries for comparable roles.

Which 3 jobs will survive AI?

Scientific Machine Learning professionals will likely continue to be in demand due to their expertise in developing and applying AI models to complex scientific problems. Roles such as data scientists, AI researchers, and machine learning engineers are expected to persist because they require specialized knowledge, critical thinking, and ongoing innovation that AI tools complement rather than replace. These jobs often involve interdisciplinary skills, programming, and understanding of domain-specific data, making them more resilient to automation.

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.

How much does a machine learning scientist make?

A machine learning scientist typically earns between $90,000 and $150,000 annually, depending on experience, education, and location. Senior roles or those with specialized skills in deep learning or natural language processing can earn higher salaries, often exceeding $180,000.

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.

Is 40 too late for data science?

Scientific Machine Learning roles often value skills and experience over age, and many professionals transition into data science or machine learning at various stages of their careers. Learning relevant tools like Python, TensorFlow, or scikit-learn and gaining practical experience can help regardless of age, making 40 not too late to pursue this field.
What are popular job titles related to Scientific Machine Learning jobs in Alabama? For Scientific Machine Learning jobs in Alabama, the most frequently searched job titles are:
What job categories do people searching Scientific Machine Learning jobs in Alabama look for? The top searched job categories for Scientific Machine Learning jobs in Alabama are:
What cities in Alabama are hiring for Scientific Machine Learning jobs? Cities in Alabama with the most Scientific Machine Learning job openings:
Scientific Machine Learning jobs near you
Data Scientist / Machine Learning Engineer

Data Scientist / Machine Learning Engineer

NaphCare

Birmingham, AL • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted yesterday

NaphCare rating

5.9

Company rating: 5.9 out of 10

Based on 47 frontline employees who took The Breakroom Quiz

753rd of 874 rated healthcare providers

Job description

Overview
We are looking for a Data Scientist / Machine Learning Engineer to join our team on-site with the NaphCare Charitable Foundation located in Birmingham, AL 35216.
Candidates local to Birmingham preferred. US Citizen or Green Card candidates only.
As a Data Scientist at the NaphCare Charitable Foundation, you will work with advanced hardware, software, and techniques to develop computational algorithms and statistical methods that find patterns and relationships in large volumes of healthcare data. The core contributions of the Data Scientist will consist of collaborating with a multi-disciplinary team, defining experimentation setups, researching data-driven solutions to the problems identified, providing technical mentorship to other team members, and communicating results to stakeholders. The Data Scientist will join a team of engineers, researchers and product owners to deliver innovative, automated, and technologically advanced healthcare solutions through the integration of predictive models and analytical insight.
Responsibilities
  • Design and implement metrics, pipelines and tools that will enable engineers to achieve their data insights.
  • Make strategic recommendations on data collection, integration and retention incorporating business requirements and knowledge of best practices.
  • Keep up to date on related technologies and frameworks, and propose new ones that the team could leverage.
  • Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
  • Summarize and clearly communicate data analysis assumptions and results
  • Identify shifts, determine new ways of looking at data, and creatively drive improvements in products.
  • Build and prototype analysis pipelines to iteratively test hypothesis.
  • Interact cross-functionally, making business recommendations to stakeholders.

Qualifications
  • Experience with distributed processing technologies
  • Experience with human-in-the-loop machine learning solutions
  • Medical Industry experience
  • Proven excellence in leading and contributing to Data Science projects.
  • Proven track record of pushing state of the art in the data science / machine learning space.
  • Strong communication, interpersonal skills and the fortitude to accomplish your goals.
  • Experience in leading discovery with stakeholders to identify requirements and the expected outcomes.
  • Capability to educate the organization both from technical and the business perspectives on new approaches, such as testing hypotheses and statistical validation of results.
  • Demonstrate the following scientist qualities: clarity, accuracy, precision, relevance, depth, breadth, logic, significance, fairness and aptitude for original research.
  • Comfortable working in a team environment.
  • Expert level in machine learning architecture and model development.
  • Strong working knowledge of statistical frameworks (Pandas, NumPy/SciPy, scikit-learn) (3+ years)
  • Strong working knowledge of machine learning frameworks (PyTorch, TensorFlow) (3+ years)
  • Mastery in building SQL queries
  • Experience monitoring the full life cycle of models
  • Experience with ETL pipelines
  • Strong verbal and written communication skills
  • Strong problem-solving skills to help refine problem statements and figure out how to solve them with the available data
  • Curious and driven to solve complex problems
  • Smart but humble, action oriented

Required Education
Ph.D. or Masters in the fields of Data Science, Engineering, Analytics, Mathematics, Computer Science, Statistics, Machine Learning, or other quantitative fields.
NaphCare is a family owned, healthcare technology company that has been delivering high quality healthcare to correctional facilities across the nation for over 35 years. Come join our team of over 7000 employees and growing! NaphCare pays well, offers outstanding benefits, and has an incredibly engaged corporate support team to make sure you have what you need to be truly excellent at what you do. At NaphCare Charitable Foundation, our vision is clear: drive scientific breakthroughs and societal upliftment through transformative research, educational programs, and scholarships. We conduct critical scientific research to address and understand health trends among justice-involved populations. Our dedication to innovation leads us to develop state-of-the-art patient care technology, setting new standards in healthcare efficiency and effectiveness.
NaphCare partners with correctional facilities to provide proactive, patient-focused healthcare.
NaphCare Full Time Benefits:
Prescriptions free of charge through our health plan
Health, dental & vision insurance that starts day one
We offer low cost benefits to our employees and their families
Employment Assistance Program (EAP) services
100% vested 401K and Roth with company contribution that starts day one
Tuition Assistance
Referral bonuses
On-site education
Free Continuing Education!
Term life insurance at no cost to the employee
Generous paid time off & paid holidays
With NaphCare, you'll play a critical role in our continuing mission to be the leading provider of quality healthcare in the correctional industry. If you want a career that will make a difference, choose the company that is different.
We support your growth and internal promotion. Once hired, we encourage our employees to continue to seek opportunities for advancement and leadership.
Equal Opportunity Employer: disability/veteran

What NaphCare employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About NaphCare

Sourced by ZipRecruiter

NaphCare partners with correctional facilities to provide proactive, patient-focused healthcare. We recognize that we serve a unique and diverse patient population, and our onsite teams take pride in bringing excellence in care to a population in great need. Be part of a world-class team of professionals who are revolutionizing correctional healthcare. NaphCare offers competitive compensation! Our full-time teammates have a top-notch benefits package, which includes medical, dental, vision, FREE prescriptions, flexible spending account, company-paid life and AD&D insurance with voluntary life and AD&D options, ST & LT disability, 401(k) company contribution, 20 days Paid Time Off, paid holidays, tuition assistance, employee referral bonuses, etc.

Industry

Health care and social assistance

Company size

1,001 - 5,000 Employees

Headquarters location

Birmingham, AL, US

Year founded

1989

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