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Scientific Machine Learning Jobs in Florida (NOW HIRING)

Work closely with other senior scientist to understand problem sets, physical data feature sets and ... Bachelors degree in Machine Learning, Data Science, Mathematics, or equivalent in a related ...

AI Machine Learning Scientist Location : This role requires associates to be in-office 1-2 days per week, fostering collaboration and connectivity while providing flexibility to support productivity ...

For more than 50 years, ENSCO has been providing leading-edge engineering, science and advanced ... Position Description ENSCO, Inc. is seeking a Machine Learning Engineer with direct experience and ...

Machine Learning Engineer

Melbourne, FL · On-site

$73K - $131K/yr

For more than 50 years, ENSCO has been providing leading-edge engineering, science and advanced ... Position Description ENSCO, Inc. is seeking a Machine Learning Engineer with direct experience and ...

... 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 ...

... 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 ...

... 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 ...

... 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 ...

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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 job categories do people searching Scientific Machine Learning jobs in Florida look for? The top searched job categories for Scientific Machine Learning jobs in Florida are:
What cities in Florida are hiring for Scientific Machine Learning jobs? Cities in Florida with the most Scientific Machine Learning job openings:
Infographic showing various Scientific Machine Learning job openings in Florida as of June 2026, with employment types broken down into 77% Full Time, and 23% Part Time. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution.
AI Machine Learning Scientist

AI Machine Learning Scientist

Elevance Health

Tampa, FL • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 7 days ago


Elevance Health rating

7.8

Company rating: 7.8 out of 10

Based on 334 frontline employees who took The Breakroom Quiz

164th of 261 rated insurance


Job description

Anticipated End Date:

2026-07-15

Position Title:

AI Machine Learning Scientist

Job Description:

AI Machine Learning Scientist

Location: This role requires associates to be in-office 1 day per week, fostering collaboration and connectivity, while providing flexibility to support productivity and work-life balance. This approach combines structured office engagement with the autonomy of virtual work, promoting a dynamic and adaptable workplace. Ideal candidates will be able to report to one of our Pulse Point locations in Indianapolis, IN, Atlanta, GA, Tampa, FL, or Richmond, VA. Alternate locations may be considered if candidates reside within a commuting distance from an office.

Please note that per our policy on hybrid/virtual work, candidates not within a reasonable commuting distance from the posting location(s) will not be considered for employment, unless an accommodation is granted as required by law.

The AI Machine Learning Scientist is responsible for Artificial Intelligence (AI) scientific and statistical methods to assist with product creation, development and improvement. Plays a critical role in enabling the responsible and scalable adoption of AI across the enterprise. This role is responsible for designing, developing, evaluating, and operationalizing AI and machine learning solutions, including Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agent-based systems. Help build reusable AI capabilities, evaluation frameworks, and governance processes that ensure AI systems are reliable, measurable, compliant, and aligned with Responsible AI principles. Will work closely with engineering, product, data science, and business teams to translate complex business challenges into production-ready AI solutions.

How you will make an impact:

  • Design, develop, and deploy AI/ML and Generative AI solutions that address business and operational challenges at enterprise scale.

  • Build and maintain infrastructure, pipelines, and services that connect structured and unstructured data sources for AI-driven applications.

  • Develop reusable AI capabilities including RAG pipelines, vector search, semantic retrieval, prompt orchestration, and agentic workflows.

  • Implement evaluation frameworks and automated testing strategies to measure model quality, accuracy, bias, safety, and performance.

  • Establish monitoring, observability, and governance processes to ensure AI systems remain reliable and compliant in production.

  • Collaborate with engineering and product teams to integrate AI capabilities into enterprise platforms and applications.

  • Drive adoption of Responsible AI practices by implementing evaluation standards, audit-ready documentation, and model governance controls.

  • Optimize AI systems for scalability, latency, reliability, and cost efficiency.

  • Support experimentation, benchmarking, and model comparison activities to improve decision-making and accelerate AI innovation.

  • Partner with cross-functional stakeholders to translate business requirements into production-ready AI capabilities and services.

  • Contribute to technical standards, architecture decisions, and best practices for enterprise AI engineering.

  • Develop experimental and analytic plans for machine learning algorithms and data modeling processes, use of strong baselines, and ability to accurately determine cause and effect relations.

MinimumRequirements:

Requires a Bachelor's degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.) or equivalent degree and 4 or more years of experience; or any combination of education and experience in configuration management, which would provide an equivalent background.

Preferred Skills, Capabilities and Experiences:

  • Experience building and deploying LLM- or SLM-based applications in production environments highly preferred.

  • Experience developing Retrieval-Augmented Generation (RAG) systems, semantic search, vector databases, embeddings, and prompt engineering techniques highly preferred.

  • Experience designing and implementing AI agents, tool-calling workflows, or agentic architectures highly preferred.

  • Experience evaluating AI systems using automated evaluation frameworks, benchmarking approaches, and human-in-the-loop review processes highly preferred.

  • Experience building scalable AI/ML pipelines and services using cloud-native architectures highly preferred.

  • Experience with MLOps practices including CI/CD, model deployment, monitoring, observability, drift detection, and lifecycle management highly preferred.

  • Experience with Python and modern AI/ML frameworks and libraries (e.g., PyTorch, TensorFlow, LangChain, LangGraph, LlamaIndex, Hugging Face, or equivalent) highly preferred.

  • Familiarity with Responsible AI principles, model governance, bias testing, explainability, and auditability requirements highly preferred.

  • Experience integrating AI solutions with APIs, enterprise platforms, and distributed systems preferred.

  • Experience reviewing, testing, validating, and hardening AI-generated code and AI-assisted development workflows preferred.

  • Experience supporting production AI systems, troubleshooting issues, and driving continuous improvement preferred.

  • Strong communication and collaboration skills with the ability to influence technical and non-technical stakeholders preferred.

  • Healthcare, regulated industry, or enterprise-scale AI experience preferred.

Job Level:

Non-Management Exempt

Workshift:

Job Family:

IFT > Artificial Intelligence

Please be advised that Elevance Health only accepts resumes for compensation from agencies that have a signed agreement with Elevance Health. Any unsolicited resumes, including those submitted to hiring managers, are deemed to be the property of Elevance Health.


Who We Are

Elevance Health is a health company dedicated to improving lives and communities - and making healthcare simpler. We are a Fortune 25 company with a longstanding history in the healthcare industry, looking for leaders at all levels of the organization who are passionate about making an impact on our members and the communities we serve.


How We Work

At Elevance Health, we are creating a culture that is designed to advance our strategy but will also lead to personal and professional growth for our associates. Our values and behaviors are the root of our culture. They are how we achieve our strategy, power our business outcomes and drive our shared success - for our consumers, our associates, our communities and our business.


We offer a range of market-competitive total rewards that include merit increases, paid holidays, Paid Time Off, and incentive bonus programs (unless covered by a collective bargaining agreement), medical, dental, vision, short and long term disability benefits, 401(k) +match, stock purchase plan, life insurance, wellness programs and financial education resources, to name a few.


Elevance Health operates in a Hybrid Workforce Strategy. Unless specified as primarily virtual by the hiring manager, associates are required to work at an Elevance Health location at least once per week, and potentially several times per week. Specific requirements and expectations for time onsite will be discussed as part of the hiring process.


The health of our associates and communities is a top priority for Elevance Health. We require all new candidates in certain patient/member-facing roles to become vaccinated against COVID-19 and Influenza. If you are not vaccinated, your offer will be rescinded unless you provide an acceptable explanation. Elevance Health will also follow all relevant federal, state and local laws.


Elevance Health is an Equal Employment Opportunity employer, and all qualified applicants will receive consideration for employment without regard to age, citizenship status, color, creed, disability, ethnicity, genetic information, gender (including gender identity and gender expression), marital status, national origin, race, religion, sex, sexual orientation, veteran status or any other status or condition protected by applicable federal, state, or local laws. Applicants who require accommodation to participate in the job application process should submit the following form: Accessibility Accommodation Request Form and a member of the team will be in contact. Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws, including, but not limited to, the Los Angeles County Fair Chance Ordinance and the California Fair Chance Act.


Prospective employees required to be screened under Florida law should review the education and awareness resources at HB531 | Florida Agency for Health Care Administration.


NOTE: Workday keeps job postings active through 11:59:59 PM on the day before the listed end date. Example: If the end date is 3/13, the posting will automatically come down on 3/12 at 11:59:59 PM. In other words - the job is posted until 3/13, not through 3/13.


What Elevance Health employees say

Pay

Benefits

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About Elevance Health

Sourced by ZipRecruiter

Elevance Health is a health company dedicated to improving lives and communities - and making healthcare simpler. A Fortune 20 company with a longstanding history in the healthcare industry, we are looking for leaders at all levels of the organization who are passionate about making an impact on our members and the communities we serve. You will thrive in a complex and collaborative environment where you take action and ownership to solve problems and lead change. Do you want to be part of a larger purpose and an evolving, high-performance culture that empowers you to make an impact?

Industry

Health care and social assistance

Company size

10,000+ Employees

Headquarters location

Indianapolis, IN, US

Year founded

2004

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