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Phd Machine Learning Startup Jobs (NOW HIRING)

Tacit

Machine Learning Scientist

San Francisco, CA · On-site

$180K - $270K/yr

About Tacit We are an early-stage, deep tech startup based in San Francisco, developing innovative ... PhD in computer science, machine learning, computational neuroscience, or related fields (or ...

Advatix Inc.

Machine Learning Engineer

San Mateo, CA · On-site

$110 - $165/hr

Equivalent Master's or PhD research experience will be considered. * Demonstrated success designing ... Startup Mindset * Thrives in fast‑paced, high‑ownership environments. * Comfortable wearing ...

Poesis

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

Prior experience at a frontier AI lab, agentic startup, leading hedge fund, big tech company, or ... Skill leveraging Claude Code, Codex, or other coding agents * BS/MS/PhD in Computer Science or a ...

Neurable, INC

Machine Learning

Cambridge, MA · On-site

Company Description Neurable is a funded brain-computer interface (BCI) startup spun out of the ... expert and PhD neuroscience, enables people to control hardware and software in real-time with ...

Neurable, INC

Machine Learning

Cambridge, MA

Company Description Neurable is a funded brain-computer interface (BCI) startup spun out of the ... expert and PhD neuroscience, enables people to control hardware and software in real-time with ...

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Phd Machine Learning Startup information

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$25.5K

$42.6K

$88K

How much do phd machine learning startup jobs pay per year?

As of Aug 10, 2026, the average yearly pay for phd machine learning startup in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

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.

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.
More about Phd Machine Learning Startup jobs
What cities are hiring for Phd Machine Learning Startup jobs? Cities with the most Phd Machine Learning Startup job openings:
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What job categories do people searching Phd Machine Learning Startup jobs look for? The top searched job categories for Phd Machine Learning Startup jobs are:
Phd Machine Learning Startup jobs near you
Infographic showing various Phd Machine Learning Startup job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Machine Learning Internship - PhD: 2027

Susquehanna International Group, LLP

Philadelphia, PA • On-site

Full-time, Internship

Re-posted 3 days ago

Job description

Overview
Our Machine Learning PhD Internship is a 10-week immersive experience designed for PhD candidates who are passionate about solving high-impact problems at the intersection of data, algorithms, and markets.
As a Machine Learning Intern at Susquehanna, you'll work on high-impact projects that closely reflect the challenges and workflows of our full-time research team. You'll apply your technical expertise in machine learning and data science to real-world financial problems, while developing a deep understanding of how machine learning integrates into Susquehanna's research and trading systems. You will leverage vast and diverse datasets and apply cutting-edge machine learning at scale to drive data-informed decisions in predictive modeling to strategic execution.
What You Can Expect
  • Conduct research and develop ML models to identify patterns in noisy, non-stationary data
  • Work side-by-side with our Machine Learning team on real, impactful problems in quantitative trading and finance, bridging the gap between cutting-edge ML research and practical implementation
  • Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches
  • Design and run experiments using the latest ML tools and frameworks
  • One-on-one mentorship from experienced researchers and technologists
  • Participate in a comprehensive education program with deep dives into Susquehanna's ML, quant, and trading practices
  • Apply rigorous scientific methods to extract signals from complex datasets and shape our understanding of market behavior
  • Explore various aspects of machine learning in quantitative finance from alpha generation and signal processing to model deployment and risk-aware decision making

What we're looking for
  • Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, Physics, Applied Mathematics, or a closely related field
  • Proven experience applying machine learning techniques in a professional or academic setting
  • Strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR
  • Hands-on experience with machine learning frameworks, including PyTorch and TensorFlow
  • Deep interest in solving complex problems and a drive to innovate in a fast-paced, competitive environment

Why Join Us?
  • Work with a world-class team of researchers and technologists
  • Access to unparalleled financial data and computing resources
  • Opportunity to make a direct impact on trading performance
  • Collaborative, intellectually stimulating environment with global reach

About Susquehanna
Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting-edge technology, we excel in solving complex problems and pushing boundaries together.
If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.

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