ZipRecruiter

Log In

1

Scientific Machine Learning Jobs in Florida (NOW HIRING)

Crowe LLP

Machine Learning Intern

Tampa, FL · On-site

$27 - $42/hr

Role Summary The data science (DS) internship at Crowe follows the firmwide calendar, approximately overlapping the academic summer. DS interns will have a designated data scientist mentor and will ...

Crowe LLP

Machine Learning Intern

Fort Lauderdale, FL · On-site

$27 - $42/hr

Role Summary The data science (DS) internship at Crowe follows the firmwide calendar, approximately overlapping the academic summer. DS interns will have a designated data scientist mentor and will ...

Crowe LLP

Machine Learning Intern

Miami, FL

$27 - $42/hr

Role Summary The data science (DS) internship at Crowe follows the firmwide calendar, approximately overlapping the academic summer. DS interns will have a designated data scientist mentor and will ...

Crowe LLP

Machine Learning Intern

Tampa, FL · On-site

$27 - $42/hr

Role Summary The data science (DS) internship at Crowe follows the firmwide calendar, approximately overlapping the academic summer. DS interns will have a designated data scientist mentor and will ...

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 ...

previous page

Showing results 41-60

All JobsScientific Machine Learning JobsScientific Machine Learning Jobs in Florida

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 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 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 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 Florida?

For Scientific Machine Learning jobs in Florida, the most frequently searched job titles are:

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:

Scientific Machine Learning jobs near you
Infographic showing various Scientific Machine Learning job openings in Florida as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 22% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Senior Director, Machine Learning and Artificial Intelligence

ADT Security Services

Boca Raton, FL • Remote

Full-time

Re-posted 4 days ago

ADT rating

7.0

Company rating: 7.0 out of 10

Based on 139 frontline employees who took The Breakroom Quiz

44th of 116 rated security

Job description

Summary:

The Senior Director of Machine Learning and Artificial Intelligence will be a strategic leader responsible for driving the development and execution of our machine learning and broader artificial intelligence initiatives. This individual will lead a team of machine learning engineers, AI engineers, and researchers to build and deploy cutting-edge ML models and AI solutions that create business value and enhance our products and services. 

The ideal candidate will have a strong technical background in machine learning and artificial intelligence, extensive leadership experience, and a proven track record of delivering impactful enterprise-grade AI solutions. This role requires working closely with business partners while understanding and working within the constraints of the business to maintain a competitive technological edge.

Duties and Responsibilities:

  • Team Leadership: Lead and mentor a team of machine learning and AI engineers, fostering a culture of innovation, continuous learning, and excellence. 
  • Strategic Roadmap: Define and execute the comprehensive ML/AI strategy and roadmap, aligning it with the company's overall business objectives and long-term vision. 
  • End-to-End Deployment: Oversee the end-to-end development and deployment of machine learning and artificial intelligence models, from ideation and experimentation to production and monitoring.
  • Cross-Functional Collaboration: Collaborate with product, engineering, data platform, and other cross-functional teams to identify new opportunities for leveraging traditional ML and advanced AI. 
  • AI Innovation & Adoption: Stay up-to-date with the latest advancements in machine learning and AI (including Generative AI, Large Language Models, and computer vision), and drive the adoption of new technologies and best practices. 
  • AI Governance & Ethics: Establish and champion frameworks for responsible AI, ethics, data privacy, and compliance across all model deployments.
  • Stakeholder Communication: Communicate the complex value and business impact of machine learning and AI initiatives to senior leadership, C-suite executives, and other stakeholders. 
  • Roadmap Influence: Influence product and operational roadmaps with actionable data insights and active AI deployments. 
  • Data Strategy: Build a strategic learning roadmap based on data observations, strategic imperatives, and developed hypotheses, while managing robust data and feature pipelines. 
  • Education: Master's degree or Ph.D. in Computer Science, Machine Learning, Artificial Intelligence, Mathematics, or a related technical field. 
  • Domain Experience: 10+ years of experience in machine learning and AI, with a proven track record of building, scaling, and deploying production-level models. 
  • Leadership Experience: 5+ years of experience leading and managing high-performing machine learning or AI engineering and research teams. 
  • Technical Expertise: Deep expertise in a variety of machine learning and AI techniques, including deep learning, natural language processing (NLP), reinforcement learning, and Generative AI/Large Language Models (LLMs). 
  • Programming & Frameworks: Strong programming skills in Python and deep experience with ML/AI frameworks such as TensorFlow, PyTorch, or Hugging Face. 
  • Core Skills: Excellent leadership, communication, and project management skills. 
  • Organizational Scaling: Demonstrated success in building and scaling ML/AI organizations from the ground up, including hiring, budgeting, and tool/vendor selection.     
  • Executive Presence: Proven ability to link ML and AI initiatives to P&L outcomes, with experience presenting comprehensive AI strategies to C-suite executives or Board members. 
  • Infrastructure Knowledge: High-level architectural understanding of MLOps, LLMOps, cloud infrastructure (AWS/GCP/Azure), and the full model development lifecycle (MDLC). 

Minimum Qualifications:

Communication Skills:

  • Writing, Talking/Hearing on the phone (Continually=67-100% of workday)

Environment Requirements: 

  • Remote/Home office (Continually=67-100% of the workday)

Travel:

  • Occasionally, less than 25%

What ADT employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

ADT logo

About ADT

Sourced by ZipRecruiter

At ADT Commercial, we are in the business of helping people and organizations to protect what matters most to them. Building upon ADT's 145-year legacy, we secure the livelihoods and futures of critical commercial environments, retail location, educational campuses, healthcare facilities and financial institutions across the U.S. as an industry-leading security, fire and life safety systems integrator. We strive to have the most experienced and technically trained and talented teams in the industry, driven by excellence at every turn. At ADT Commercial, we truly believe that our people are the difference - for our organization, the customers we serve and the communities we protect. When you're a part of ADT Commercial, you'll have the opportunity to be a part of that difference every day. With more than 300 locations, a deep national presence, and comprehensive portfolio of solutions and services, our employees are always poised for career advancement and growth. For more information, visit www.adtcommercial.com or follow us on LinkedIn and Facebook.

Industry

Personal services

Company size

10,000+ Employees

Headquarters location

Boca Raton, FL, US

Year founded

1874

View All ADT Jobs

Apply