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Phd Machine Learning Startup Jobs in Oklahoma (NOW HIRING)

Camgian Corporation

Senior AI Engineer

Lawton, OK · On-site

$100 - $130/hr

We are focused on applying state-of-the-art Artificial Intelligence, Machine Learning, Computer ... Master's or PhD in a computer science related discipline * Experience with developing and deploying ...

Camgian Corporation

Senior AI Engineer

Lawton, OK · On-site

$102K - $141K/yr

We are focused on applying state-of-the-art Artificial Intelligence, Machine Learning, Computer ... Master's or PhD in a computer science related discipline * Experience with developing and deploying ...

Camgian Corporation

Senior AI Engineer

Lawton, OK · On-site

$102K - $141K/yr

We are focused on applying state-of-the-art Artificial Intelligence, Machine Learning, Computer ... Master's or PhD in a computer science related discipline * Experience with developing and deploying ...

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Phd Machine Learning Startup information

What does a PhD machine learning professional do at a startup?

PhD holders in Machine Learning at startups typically lead research and development efforts to create innovative algorithms and models that solve real-world problems. They often work on designing and implementing advanced machine learning solutions, analyzing large datasets, and collaborating with product and engineering teams to bring research ideas to production. Their expertise helps startups stay competitive by driving technological advancements and fostering a culture of innovation.

What skills and qualifications are needed to thrive as a PhD machine learning professional in a startup?

To excel as a PhD-level Machine Learning professional at a startup, you need advanced expertise in machine learning algorithms, statistical modeling, and a doctoral degree in a related field. Experience with Python, TensorFlow, PyTorch, and version control systems, along with a strong publication record, is typically expected. Initiative, adaptability, and excellent problem-solving and communication abilities are crucial soft skills in the fast-paced startup setting. These competencies enable rapid innovation, effective team collaboration, and successful deployment of machine learning solutions under resource constraints.

What are common challenges faced by PhD machine learning professionals in startups?

PhD-level professionals in machine learning startups often encounter challenges such as balancing research innovation with the need for rapid product development. Unlike academia, startups prioritize practical solutions that fit tight deadlines and resource constraints. Team members typically wear multiple hats and collaborate closely with engineers, product managers, and business stakeholders, requiring strong communication skills and adaptability. Additionally, translating cutting-edge research into scalable, real-world applications can be both intellectually rewarding and demanding.

How much does a PhD in machine learning make?

A PhD in machine learning working at a startup or tech company typically earns between $100,000 and $150,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in deep learning or AI may command higher salaries, especially in competitive markets.

What can you do with a PhD in machine learning?

A PhD in machine learning prepares individuals for advanced roles such as research scientist, machine learning engineer, or data scientist in startups and tech companies. It enables expertise in developing algorithms, analyzing large datasets, and deploying AI models using tools like Python, TensorFlow, or PyTorch. These roles often require strong programming skills, knowledge of statistical methods, and the ability to work on innovative AI solutions.

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Phd Machine Learning Startup jobs near you

AI Trainer - Microbiology Expert

micro1 AI

Edmond, OK • Remote

$70 - $90/hr

Part-time

Re-posted 8 days ago

Job description

Role Title: Microbiologist


Role Type: Contractor


Location: Remote


micro1 is engaging Microbiologists to contribute their scientific expertise to a unique 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 — your domain knowledge is what matters.


Key Responsibilities:

  1. Investigate and analyze the development, morphology, and behavior of microscopic organisms including bacteria, fungi, and algae.
  2. Contribute to the study of the relationship between microorganisms and disease, supporting projects involving medical microbiology.
  3. Assess the impact of antibiotics and other agents on microbial populations, providing insights for AI model accuracy.
  4. Document experimental findings and processes with a focus on clarity for AI training data.
  5. Collaborate with interdisciplinary teams to ensure scientific rigor and data integrity in AI development.
  6. Provide written and verbal expertise on microbiological phenomena and their relevance to real-world and computational contexts.
  7. Utilize rubrics and established evaluation criteria to assess data quality and support AI training workflows.


Required Skills and Qualifications:

  1. Bachelor’s degree or higher in Biology, Microbiology, Chemistry, or a related field.
  2. Extensive knowledge of bacterial, fungal, and algal systems.
  3. Demonstrated expertise in investigating microbial structure and physiology.
  4. Strong written and verbal communication skills for technical and interdisciplinary collaboration.
  5. Ability to document processes and findings clearly for integration into AI systems.
  6. Comfort working independently in a fully remote, digital-first environment.
  7. Attention to detail and commitment to scientific accuracy.


Preferred Qualifications:

  1. Prior experience developing or applying rubrics in scientific or educational contexts.
  2. Experience with AI, machine learning, or annotation projects related to biology or microbiology.
  3. Advanced degree (Master’s or PhD) in a relevant field.

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