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Executive Full Stack Machine Learning Engineer Jobs in New York

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Machine Learning Engineer

New York, NY · Hybrid

$90K - $254K/yr

Collaborate closely with product managers, full-stack engineers, and TPMs to ensure seamless ... Expertise in machine learning techniques, including but not limited to regression, classification ...

Forhyre

Machine Learning Engineer

New York, NY

We are looking for a Machine Learning Engineer to help us create artificial intelligence products. Machine Learning Engineer responsibilities include creating machine learning models and retraining ...

Quanta Search

Machine Learning Engineer

Manhattan, NY · On-site

Machine Learning Engineers build production grade machine learning algorithms that operate in real time or at scale. They have a very deep understanding of machine learning algorithms and cloud ...

Quanta Search

Machine Learning Engineer

Manhattan, NY · On-site

Machine Learning Engineers build production grade machine learning algorithms that operate in real time or at scale. They have a very deep understanding of machine learning algorithms and cloud ...

Hang

Machine Learning Engineer

New York, NY · On-site +1

About the Role We are seeking a skilled and innovative Machine Learning Engineer to join our team. This person will implement and develop machine learning models to enhance our platform ...

Autodesk

Senior Machine Learning Engineer

New York, NY · On-site +1

$114K - $157K/yr

This role is designed for someone who enjoys working across the full machine learning lifecycle and ... Proficiency with the Python machine learning stack, including tools such as Pandas, NumPy, and ...

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Executive Full Stack Machine Learning Engineer information

Will AI replace full-stack dev?

As an Executive Full Stack Machine Learning Engineer, it is unlikely that AI will fully replace full-stack developers, as their roles require complex problem-solving, creativity, and understanding of business needs that AI cannot replicate. AI tools can automate certain coding tasks and improve efficiency, but human oversight and expertise remain essential for designing, integrating, and maintaining full-stack applications. The evolving landscape emphasizes collaboration between AI and developers rather than replacement.

What engineer makes $500,000 a year?

An executive full stack machine learning engineer can earn $500,000 or more annually, especially with extensive experience, advanced skills in AI and software development, and working at large tech companies or startups with competitive compensation packages. High salaries often include base pay, bonuses, and stock options, reflecting seniority and expertise in the field.

Will MLE be replaced by AI?

An Executive Full Stack Machine Learning Engineer designs and implements AI systems, but AI is a tool that complements rather than replaces such roles. While automation and AI advancements can handle certain tasks, skilled engineers are needed for developing, maintaining, and improving complex machine learning solutions. Continuous learning and expertise in programming, data analysis, and model deployment remain essential in this field.

What is the salary of full-stack machine learning engineer?

The salary of a full-stack machine learning engineer typically ranges from $100,000 to $150,000 annually, depending on experience, location, and company size. Senior roles or those requiring specialized skills in deep learning or cloud platforms may offer higher compensation.

What is the difference between Executive Full Stack Machine Learning Engineer vs Data Scientist?

AspectExecutive Full Stack Machine Learning EngineerData Scientist
CredentialsBachelor's/Master's in CS, Engineering, or related; often requires experience in ML and full stack developmentBachelor's/Master's in Data Science, Statistics, or related; strong analytical and statistical skills
Work EnvironmentDevelops end-to-end ML solutions, integrates backend and frontend, collaborates with engineering teamsAnalyzes data, builds models, visualizes insights, often in research or analytics teams
Industry UsageUsed in tech companies, startups, and enterprises deploying ML productsCommon in research institutions, analytics firms, and data-driven organizations

The Executive Full Stack Machine Learning Engineer focuses on building and deploying complete ML solutions, combining software engineering and data science skills. In contrast, Data Scientists primarily analyze data and develop models without necessarily handling full stack development. Both roles require strong technical credentials but differ in scope and daily tasks.

What are the most commonly searched types of Full Stack Machine Learning Engineer jobs in New York? The most popular types of Full Stack Machine Learning Engineer jobs in New York are:
What are popular job titles related to Executive Full Stack Machine Learning Engineer jobs in New York? For Executive Full Stack Machine Learning Engineer jobs in New York, the most frequently searched job titles are:
What job categories do people searching Executive Full Stack Machine Learning Engineer jobs in New York look for? The top searched job categories for Executive Full Stack Machine Learning Engineer jobs in New York are:
What cities in New York are hiring for Executive Full Stack Machine Learning Engineer jobs? Cities in New York with the most Executive Full Stack Machine Learning Engineer job openings:
Executive Full Stack Machine Learning Engineer jobs near you
Infographic showing various Executive Full Stack Machine Learning Engineer job openings in New York as of June 2026, with employment types broken down into 96% Full Time, 1% Part Time, 2% Temporary, and 1% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

Graham Capital Management, L.P.

Manhattan, NY • On-site

Full-time

Posted 18 days ago

Job description

Job Summary:
Graham Capital Management, L.P. is an alternative investment manager specializing in discretionary and quantitative macro strategies. They are seeking a Machine Learning Engineer to join their Data Science team, where the role involves developing innovative solutions using machine learning and advanced statistical methods to support quantitative research and trading operations.
Responsibilities:
• You will be part of a growing team within Data Science.
• You will work alongside world-class talent to find innovative solutions to some of the most interesting problems in the buy-side.
• You will work closely with other areas such as Technology, Quantitative Research and Portfolio Manager groups as well as Risk and Operations to learn about problems they face with respect to data and ultimately develop cutting edge solutions.
• Your focus will be to dive deep into multiple data sets to understand relationships, develop time series, forecasting models, and support quant strategies, and provide new insights and leverage state-of-the-art machine learning and advanced statistical methods to produce the best data sources for the fund.
Qualifications:
Required:
• Undergraduate or higher degree in Computer Science, Engineering, Operations Research, or other quantitative discipline
• 3+ years of hands-on experience with Machine Learning and Statistics on large, unstructured, data sets
• Experience writing production code for multi-client systems serving model results is a great plus
• Ability to clearly communicate research findings to technical and nontechnical stakeholders
• Full-stack experience with Python (preferred) or C++, Spark/Scala, SQL or other distributed data processing technologies as well as experience working comfortably building and deploying services and models in containerized environments
• Experience with scientific computing, statistics, optimization, time series, panel data, etc.
• Comfortable handling multiple projects to solve varied problems working with multiple teams
• Detail-oriented mindset
• Sense of ownership of his/her work, working well both independently as well as collaboratively
Company:
Who We Are & What We Do: Graham Capital Management, L.P. Founded in 1994, the company is headquartered in Norwalk, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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