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Machine Learning Software Engineer Jobs (NOW HIRING)

Point72

Machine Learning Engineer

New York, NY

Experience with machine learning software libraries such as TensorFlow or PyTorch * Experience implementing Agent or Context engineering is strongly preferred * Experience with natural language ...

Stellar Cyber

Senior Staff Software Engineer

$125K - $165K/yr

Position Overview We are looking for a highly skilled Senior Machine Learning Software Engineer with a passion for building robust and scalable systems to power Stellar Cyber's Open XDR platform. In ...

Moffitt

Research Software Engineer

Long Beach, CA

$215K/yr

Summary The Machine Learning Engineer provides an array of services to support the Department of ... We are looking for a motivated individual to develop open-source software for biomedical data ...

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Machine Learning Software Engineer information

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$63.5K

$147.5K

$205.5K

How much do machine learning software engineer jobs pay per year?

As of Jul 9, 2026, the average yearly pay for machine learning software engineer in the United States is $147,524.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,000.00 and $173,000.00 per year, depending on experience, location, and employer.

What does a Machine Learning Software Engineer do?

A Machine Learning Software Engineer designs, develops, and deploys machine learning models within software applications. They work on data preprocessing, model training, optimization, and integration into production systems. Their role requires expertise in programming (Python, Java, or C++), machine learning frameworks (TensorFlow, PyTorch, or Scikit-learn), and cloud platforms. They collaborate with data scientists and software engineers to build scalable ML solutions.

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

To thrive as a Machine Learning Software Engineer, you need a solid understanding of programming (especially Python), algorithms, data structures, and mathematics, ideally backed by a degree in computer science, engineering, or a related field. Experience with frameworks such as TensorFlow or PyTorch, familiarity with cloud platforms (AWS, Azure, or GCP), and relevant certifications in data science or machine learning are highly valuable. Strong problem-solving skills, effective communication, and the ability to work collaboratively with cross-functional teams set outstanding candidates apart. These competencies are crucial for building deployable, scalable, and maintainable machine learning solutions that address real business challenges.

What are the day-to-day responsibilities of a Machine Learning Software Engineer?

As a Machine Learning Software Engineer, your daily tasks typically include developing and optimizing machine learning models, collaborating with data scientists and product teams to define requirements, and integrating models into production systems. You’ll work extensively with large datasets to preprocess, analyze, and validate data, as well as monitor model performance and iterate on solutions when needed. It's common to participate in code reviews, contribute to architectural decisions, and maintain documentation for reproducibility and knowledge sharing. This role offers a dynamic and intellectually stimulating environment, making it ideal for those who enjoy solving complex technical problems and working at the intersection of engineering and data science.

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Machine Learning Software Engineer jobs near you
Infographic showing various Machine Learning Software Engineer job openings in the United States as of July 2026, with employment types broken down into 95% Full Time, 2% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $147,524 per year, or $70.9 per hour.
Machine Learning Engineer

Machine Learning Engineer

Point72

New York, NY

Other

Re-posted 25 days ago

Job description

About Cubist

Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.

Role/Responsibilities:

We are seeking a Machine Learning Engineer to join the High Frequency Trading Technology team.

This role will apply the latest AI technologies to solve various real-world problems and streamline day-to-day operations, such as creating a production support AI agent that helps monitor production problems and suggest actions.

This role will also work with the AI research group on various projects such as creating synthetic data for training and using MCP agents to streamline research workflow.

Requirements:

  • PhD or PhD candidate in machine learning, computer science or other AI related research fields
  • Experience with sequential modeling and time series forecasting using deep learning
  • Experience with deep neural networks and representation learning
  • Prior experience working in a data driven research environment
  • Experience with translating mathematical models and algorithms into code
  • Proficiency in programming languages such as Python and R
  • Experience with machine learning software libraries such as TensorFlow or PyTorch
  • Experience implementing Agent or Context engineering is strongly preferred
  • Experience with natural language processing technology is strongly preferred
  • Excellent analytical skills, with strong attention to detail
  • Collaborative mindset with strong independent research ability
  • Strong written and verbal communication skills
  • Commitment to the highest ethical standards

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