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Phd Machine Learning Startup Jobs in California (NOW HIRING)

Machine Learning Scientist

Irvine, CA · On-site

$140 - $200/hr

AI is a National Science Foundation (NSF) and investor-funded startup based in Orange County, California. Our machine learning team currently consists of 3 PhDs in Computer Vision.We are looking for ...

Nace AI is a company focused on machine learning solutions, and they are seeking a Machine Learning ... Preferred : • MS/PhD in CS or related technical field. • Familiarity with data processing ...

... fast-paced startup environments. This leader should have a strong coding foundation, deep ... Define and own the machine learning roadmap in alignment with business goals. * Lead the ML ...

OR PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field. • 6+ months of academic and/or work experience developing and/or optimizing machine learning models ...

Machine Learning Researcher

San Diego, CA · On-site

$159.10 - $238.70/hr

OR PhD in Computer Engineering, Computer Science, Electrical Engineering, or related field. * 6+ months of academic and/or work experience developing and/or optimizing machine learning models ...

The Machine Learning Engineer will design and develop scalable training pipelines for multimodal AI ... paced startup environment, and able to demonstrate strong ownership and urgency in execution.

They are seeking a Machine Learning Engineer to design and develop scalable training pipelines for ... paced startup environment, and able to demonstrate strong ownership and urgency in execution.

Machine Learning Engineer

Sunnyvale, CA · On-site

$150.40 - $277.60/hr

MS or PhD in computer vision, computer graphics, machine learning, computer science, computer engineering or related fields. * Self‑motivated with proven ability to effectively prioritize and ...

Showing results 41-60

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.

What job categories do people searching Phd Machine Learning Startup jobs in California look for?

The top searched job categories for Phd Machine Learning Startup jobs in California are:

What cities in California are hiring for Phd Machine Learning Startup jobs?

Cities in California with the most Phd Machine Learning Startup job openings:

Machine Learning Scientist

Steg.AI

Irvine, CA • On-site

$140 - $200/hr

Other

Posted 4 days ago


Job description

# Machine Learning ScientistIrvine, CA**Full Time — In Office — Irvine, CA**## About Steg.AISteg.AI's mission is to protect and authenticate digital media. We do it by writing software that uses AI technology to watermark digital media. Our watermarks are invisible to humans, but detectable by our proprietary algorithms.Founded in 2019, Steg.AI is a National Science Foundation (NSF) and investor-funded startup based in Orange County, California. Our machine learning team currently consists of 3 PhDs in Computer Vision.We are looking for a highly motivated machine learning scientist with a passion for groundbreaking AI technology for watermarking, steganography, or media provenance.## Job DescriptionYou will work with the machine learning team to design and implement state of the art deep learning algorithms for steganography with digital media (e.g. images, video, etc.), and work with the engineering team to deploy these algorithms to mobile, desktop, and cloud platforms.## Scope of Responsibility* Collaborate with the machine learning team to develop and implement novel steganography algorithms with deep learning* Collaborate with the engineering team to deploy models to customers* Benchmark new models versus older models* Disseminate findings to the team via written reports and oral presentations## Required Qualifications* Expert with PyTorch and training and testing deep learning models* Familiarity with dataset collection/curation for training deep networks* Strong collaboration, communication, and organizational skills## Bonus Qualifications* Familiarity with steganography and watermarking technologies* Familiarity with image/video compression algorithms* Computer Vision/Machine Learning publications in CVPR/ICCV/NeurIPS/etc.* Experience with deploying machine learning models to customers via mobile, desktop, or cloud service platforms## To ApplySend your resume/CV to **careers@steg.ai**Apply now #J-18808-Ljbffr