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Phd Machine Learning Jobs in New Port Richey, FL

Domain Expert - (STEM PhD)

Tampa, FL ยท Remote

$80 - $90/hr

PhD Engineer (Electrical, Mechanical, Chemical) Role Type: Contractor Location: Remote micro1 is ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

Engineering AI Evaluator (PhD)

Tampa, FL ยท Remote

$80 - $90/hr

PhD Engineer (Electrical, Mechanical, Chemical) Role Type: Contractor Location: Remote micro1 is ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

PhD Engineer (Electrical, Mechanical, Chemical) Role Type: Contractor Location: Remote micro1 is ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

Develops scalable, automated solutions using machine learning, simulation, and optimization to ... PhD) in mathematics, computer science, statistics, economics, finance, actuarial sciences, science ...

... machine learning, Natural Language Processing (NLP), computer vision, Large Language Models (LLMs ... Preferred Qualifications and Skills: - PhD in Data Science, Computer Science, AI, Mathematics ...

PhD completed within the last 10 years preferred. * AI/ML Expertise: Deep proficiency with modern machine learning, including deep learning, transformers, graph neural networks, generative models ...

Data Scientist

Tampa, FL ยท On-site

$130K - $140K/yr

... in Supervised, unsupervised Machine Learning (ML) algorithms, forecasting and inventory ... Master's or PhD in Statistics, CS, or related field (preferred) Job / Role Description: * Lead end ...

Phd Machine Learning information

See New Port Richey, FL salary details

$12

$20

$27

How much do phd machine learning jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for phd machine learning in New Port Richey, FL is $20.33, according to ZipRecruiter salary data. Most workers in this role earn between $17.55 and $22.69 per hour, depending on experience, location, and employer.

What is a PhD in Machine Learning?

A PhD in Machine Learning is an advanced doctoral degree focused on developing new algorithms, theories, and applications in the field of machine learning. Graduates typically conduct original research, contribute to academic publications, and often specialize in areas like deep learning, reinforcement learning, or probabilistic modeling. This degree prepares individuals for careers in academia, industry research labs, or leadership roles in tech companies. The program usually involves coursework, comprehensive exams, and the completion of a dissertation based on novel research.

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

To thrive as a PhD-level Machine Learning professional, you need deep expertise in mathematics, statistics, computer science, and advanced machine learning algorithms, typically supported by a doctoral degree. Proficiency with programming languages like Python or R, machine learning frameworks such as TensorFlow or PyTorch, and experience with large-scale data systems are essential. Strong problem-solving skills, critical thinking, and effective communication set outstanding candidates apart by enabling them to tackle complex research challenges and collaborate across teams. These skills and qualities are crucial for driving innovation, publishing research, and developing impactful machine learning solutions.

What are some common challenges faced by PhD-level professionals in machine learning when transitioning from academia to industry roles?

PhD graduates in machine learning often encounter challenges such as adapting to faster-paced project timelines, aligning research with business objectives, and collaborating in multidisciplinary teams. Unlike academia, where projects can be exploratory and long-term, industry roles usually require actionable results within shorter deadlines. Additionally, communicating complex technical ideas to non-technical stakeholders and prioritizing practical solutions over theoretical novelty are key adjustments. However, these challenges also present opportunities for professional growth and broader impact.

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

AspectPhd Machine LearningData Scientist
Required CredentialsPhD in Computer Science, AI, or related fieldBachelor's or Master's in Data Science, Statistics, or related field
Work EnvironmentResearch labs, academia, R&D departmentsBusiness, tech companies, analytics teams
Industry UsageResearch-focused roles, advanced algorithm developmentData analysis, model building, business insights
Common Search/ComparisonYesYes

While both roles involve working with data and algorithms, a Phd Machine Learning typically focuses on research, developing new models, and theoretical work, often in academic or R&D settings. A Data Scientist applies these techniques to solve practical business problems, analyze data, and generate insights in industry environments.

What cities near New Port Richey, FL are hiring for Phd Machine Learning jobs? Cities near New Port Richey, FL with the most Phd Machine Learning job openings:
Domain Expert - (STEM PhD)

Domain Expert - (STEM PhD)

micro1 AI

Tampa, FL โ€ข Remote

$80 - $90/hr

Part-time

Posted 21 days ago


Job description

Role Title: PhD Engineer (Electrical, Mechanical, Chemical)


Role Type: Contractor


Location: Remote


micro1 is engaging PhD-level Engineers in Electrical, Mechanical, or Chemical disciplines to contribute to a high-impact customer project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required โ€” your domain knowledge is what matters.


Scope of Work

  1. Deliver authoritative written responses to complex engineering prompts in your area of expertise
  2. Review and interpret scientific literature to provide contextually accurate and current insights
  3. Design and document realistic experimental scenarios based on advanced engineering principles
  4. Analyze data and interpret results to inform AI training datasets with precision
  5. Apply sophisticated calculus and quantitative methodologies to problem-solving tasks
  6. Ensure clarity, accuracy, and completeness of all submitted materials based on provided guidelines
  7. Collaborate with project coordinators to refine prompt response quality as needed


Preferred Qualifications

  1. PhD in Electrical, Mechanical, or Chemical Engineering
  2. Demonstrated expertise in calculus, data analysis, research methodology, and experimental design
  3. Exceptional written and verbal communication skills with the ability to convey complex concepts clearly
  4. Strong literature review capabilities and familiarity with synthesizing scientific knowledge
  5. Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not required)
  6. Proven ability to produce "golden response" level deliverables with accuracy and completeness
  7. Detail-oriented mindset and commitment to high-quality, impactful contributions