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Machine Learning Finance Jobs (NOW HIRING)

As a machine learning engineer in Finance, you'll play an integral and global role in building the data foundations, services, and platforms used for delivering insights and automating decisions for ...

Join a high-growth financial technology organization focused on delivering modern digital banking ... Position Summary We are seeking a Machine Learning Engineer to help design, implement, and scale AI ...

Machine Learning Engineer

San Francisco, CA ยท On-site

$200K - $280K/yr

About Poesis Whoever builds the leading intelligence for finance will create far more than returns ... About the Role At Poesis, machine learning and artificial intelligence open the door to improved ...

As a machine learning engineer in Finance, you'll play an integral and global role in building the data foundations, services, and platforms used for delivering insights and automating decisions for ...

Successful candidates will also have deep interest in learning about trading and the financial ... Machine Learning Engineers build production grade machine learning algorithms that operate in real ...

Successful candidates will also have deep interest in learning about trading and the financial ... Machine Learning Engineers build production grade machine learning algorithms that operate in real ...

Our mission is to democratize finance for all. An estimated $124 trillion of assets will be ... We're looking for an exceptional Machine Learning Engineer to help shape the future of our core ...

... your finances. And if it's career development you desire, we provide that, too! At Paylocity ... Machine Learning Engineer Position Overview Paylocity is growing its Machine Learning Engineering ...

Our mission is simple: build strong and diverse communities through innovative financial technology ... SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and ...

Our mission is simple: build strong and diverse communities through innovative financial technology ... SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and ...

Hang draws from years of deep expertise in loyalty, game design, and finance with employees from ... This person will implement and develop machine learning models to enhance our platform ...

As a machine learning engineer in Finance, you'll play an integral and global role in building the data foundations, services, and platforms used for delivering insights and automating decisions for ...

Stefanini is looking for a Machine Learning Engineer(Allen Park, MI) For quick apply, please reach ... markets, including financial services, manufacturing, telecommunications, chemical services ...

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Machine Learning Finance information

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$25K

$92.6K

$135.5K

How much do machine learning finance jobs pay per year?

As of Jul 4, 2026, the average yearly pay for machine learning finance in the United States is $92,631.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,000.00 and $109,000.00 per year, depending on experience, location, and employer.

What job makes $1,000,000 a year?

In the field of machine learning finance, highly senior roles such as Chief Data Officer or Quantitative Hedge Fund Manager can earn $1,000,000 or more annually, especially with bonuses and profit sharing. These positions typically require advanced degrees, extensive experience, and expertise in algorithms, financial modeling, and programming tools like Python or R.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence or machine learning within finance or technology sectors, often involving advanced skills in data analysis, programming, and model development. Such roles may include AI research scientists, machine learning engineers, or senior data scientists, and usually require extensive experience, specialized certifications, and proficiency with tools like Python, TensorFlow, or cloud platforms.

Can machine learning be used in finance?

Machine learning is widely used in finance for tasks such as risk assessment, fraud detection, algorithmic trading, and portfolio management. Machine learning finance professionals develop models using programming languages like Python and tools such as TensorFlow or scikit-learn to analyze large datasets and improve decision-making processes.

What are the key skills and qualifications needed to thrive in the Machine Learning Finance position, and why are they important?

To excel in Machine Learning Finance, you need strong quantitative skills, proficiency in programming (typically Python or R), and a solid background in both finance and machine learning, often supported by a relevant degree such as in computer science, statistics, mathematics, or finance. Familiarity with machine learning libraries (like TensorFlow, scikit-learn), financial modeling tools, and certifications such as CFA or FRM can be highly beneficial. Excellent problem-solving abilities, communication skills, and a collaborative attitude help professionals translate complex data into practical financial insights and work effectively with both technical and non-technical stakeholders. These competencies enable you to create robust predictive models, drive innovation in financial analysis, and ensure sound decision-making in dynamic industry settings.

What is the salary of ML in finance?

Machine Learning professionals in finance typically earn between $80,000 and $150,000 annually, depending on experience, location, and specific role. Senior roles or those with advanced skills in data analysis, programming, and financial modeling can earn higher salaries, often exceeding $200,000 with bonuses and incentives.

What are some typical challenges faced by professionals in Machine Learning Finance roles?

Professionals in Machine Learning Finance often encounter challenges such as working with noisy or incomplete financial data, keeping up with rapidly evolving algorithms, and ensuring model compliance with industry regulations. They may also need to bridge the gap between technical model development and practical business needs, communicating complex findings to non-technical teams. These roles typically involve close collaboration with traders, financial analysts, and risk managers to ensure that machine learning solutions are both accurate and actionable. Facing these challenges can be rewarding, offering significant opportunities for skill development and career advancement in a data-driven financial landscape.

What is a Machine Learning Finance job?

A Machine Learning Finance job involves applying machine learning techniques to financial problems such as risk assessment, algorithmic trading, fraud detection, and portfolio optimization. Professionals in this field build predictive models, analyze large datasets, and automate decision-making processes to improve financial performance. They typically work with tools like Python, TensorFlow, and financial datasets to develop AI-driven solutions. These roles require expertise in machine learning, statistics, and financial markets, often blending data science with quantitative finance.

What cities are hiring for Machine Learning Finance jobs? Cities with the most Machine Learning Finance job openings:
What are the most commonly searched types of Machine Learning Finance jobs? The most popular types of Machine Learning Finance jobs are:
What states have the most Machine Learning Finance jobs? States with the most job openings for Machine Learning Finance jobs include:
Infographic showing various Machine Learning Finance job openings in the United States as of June 2026, with employment types broken down into 96% Full Time, 3% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $92,631 per year, or $44.5 per hour.
Machine Learning Internship - PhD: 2027

Machine Learning Internship - PhD: 2027

Susquehanna International Group, LLP

Philadelphia, PA โ€ข On-site

Full-time, Internship

Posted 26 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.