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Machine Learning Engineer Jobs in Huntington, NY

All Cloud BSD

Machine Learning Engineer

Manhattan, NY · On-site

$120 - $180/hr

Description Machine Learning Engineer Location: US / Canada (Eastern Time) - Home-based Job Type: Full-time, Permanent About AllCloud AllCloud is a leader in amplifying organizations' cloud potential ...

New

Capital One

Lead Machine Learning Engineer (IC)

New York, NY · On-site

$112K - $147K/yr

Lead Machine Learning Engineer (IC) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.

New

Capital One

Lead Machine Learning Engineer (IC)

New York, NY · On-site +1

$112K - $147K/yr

Lead Machine Learning Engineer (IC) As a Capital One Machine Learning Engineer (MLE), you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.

New

S&P Global, Inc.

Machine Learning Engineer

Manhattan, NY · On-site

$209 - $250.30/hr

Machine Learning Engineer Location: 55 Water Street, New York, NY 10041 (Telecommuting permitted within normal commuting distance of New York, NY office) Job Duties * Kensho Technologies LLC seeks a ...

New

Canals

Machine Learning Engineer

New York, NY · Remote

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining high quality, owning end-to-end ML pipelines while shaping product features that deliver real-world ...

Canals

Machine Learning Engineer

New York, NY · On-site

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining high quality, owning end-to-end ML pipelines while shaping product features that deliver real-world ...

Canals, Inc.

Machine Learning Engineer

Manhattan, NY · On-site

$120/hr

We're looking for a senior-level Machine Learning Engineer who can move quickly while maintaining high quality, owning end-to-end ML pipelines while shaping product features that deliver real-world ...

Jane Street

Machine Learning Engineer

New York, NY · On-site

We are looking for an engineer with robust experience in machine learning and strong mathematical foundations to join our growing ML team and to help drive the direction of our ML platform. Machine ...

Spgi

Machine Learning Engineer

New York, NY · On-site +1

$209K - $250K/yr

Machine Learning Engineer Location: 55 Water Street, New York, NY 10041 (Telecommuting permitted within normal commuting distance of New York, NY office) Job Duties: Kensho Technologies LLC seeks a ...

Jane Street

Machine Learning Engineer

New York, NY

We are looking for an engineer with robust experience in machine learning and strong mathematical foundations to join our growing ML team and to help drive the direction of our ML platform. Machine ...

Root Access, Inc.

Machine Learning Engineer

Manhattan, NY · On-site

$140 - $190/hr

Our team is a passionate mix of engineers across electrical, firmware, software, and machine learning. Core Responsibilities * Architect Physics Foundation Models: Design and train deep learning ...

WireScreen

Machine Learning Engineer

Manhattan, NY · On-site

$120 - $150/hr

As a Machine Learning Engineer at WireScreen, you will be working across our data systems to unlock the source of truth behind one of the world's economic powerhouses: China. This role is critical to ...

Visible Hands

Machine Learning Engineer

Manhattan, NY · On-site

$150 - $190/hr

Our team is a passionate mix of engineers across electrical, firmware, software, and machine learning. Core Responsibilities * Architect Physics Foundation Models: Design and train deep learning ...

New

exacare ai

Machine Learning Engineer

New York, NY · On-site

About the Role We are looking for a Machine Learning Engineer, MLOps to help operationalize and scale our machine learning systems. This is an engineering-focused role centered on building the ...

Capital One

Sr. Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

Sr. Lead Machine Learning Engineer As a Capital One Machine Learning Engineer (MLE) , you'll be part of an Agile team dedicated to productionizing machine learning applications and systems at scale.

Root Access Inc

Machine Learning Engineer

New York, NY · On-site

Our team is a passionate mix of engineers across electrical, firmware, software, and machine learning. Core Responsibilities * Architect Physics Foundation Models: Design and train deep learning ...

Virtu Financial

Machine Learning Engineer

New York, NY

$200K - $300K/yr

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a small group of technologists whose primary function is building the infrastructure that powers our ...

Virtu Financial

Machine Learning Engineer

New York, NY · On-site

$200K - $300K/yr

Virtu's Research Technology team is looking for an experienced Machine Learning Engineer to join a small group of technologists whose primary function is building the infrastructure that powers our ...

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Showing results 21-40

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Huntington, NY

Machine Learning Engineer information

See Huntington, NY salary details

$33.3K

$136.3K

$204.7K

How much do machine learning engineer jobs pay per year?

As of Aug 7, 2026, the average yearly pay for machine learning engineer in Huntington, NY is $136,254.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,400.00 and $164,000.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by machine learning engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
What are popular job titles related to Machine Learning Engineer jobs in Huntington, NY? For Machine Learning Engineer jobs in Huntington, NY, the most frequently searched job titles are:
What cities near Huntington, NY are hiring for Machine Learning Engineer jobs? Cities near Huntington, NY with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Huntington, NY as of July 2026, with employment types broken down into 1% As Needed, 71% Full Time, 23% Part Time, 1% Temporary, and 4% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution, with an average salary of $136,254 per year, or $65.5 per hour.

Applied Machine Learning Engineer

Fireworks AI

New York, NY • On-site

Other

Re-posted 20 days ago

Job description

The Role:

As an Applied Machine Learning Engineer, you will serve as a vital bridge between cutting-edge AI research and practical, real-world applications. Your work will focus on developing, fine-tuning, and operationalizing machine learning models that drive business value and enhance user experiences. This is a hands-on engineering role that combines deep technical expertise with a strong customer focus to deliver scalable AI solutions.

Key Responsibilities:
  • Customer Success: Collaborate directly with the GTM team (Account Executives and Solutions Architects) to ensure smooth integration and successful deployment of ML solutions.
  • Demo / Proof of Concept (PoC): Build and present compelling PoCs that demonstrate the capabilities of our AI technology.
  • Application Build: Design, develop, and deploy end-to-end AI-powered applications tailored to customer needs.
  • Platform Features / Bug Fixes: Contribute to the internal ML platform, including adding features and resolving issues.
  • New Model Enablements: Integrate and enable new machine learning models into the existing platform or client environments.
  • Performance Optimizations: Improve system performance, efficiency, and scalability of deployed models and applications.
  • Partnership Enablement: Work closely with partners to enable joint AI solutions and ensure seamless collaboration.
Minimum Qualifications:
  • Bachelor's degree in Computer Science, Engineering, or a related technical field.
  • 5+ years of experience in a software engineering role, with a strong preference for customer-facing roles.
  • Robust coding skills required, preferably with proficiency in Python.
  • Demonstrated ability to lead and execute complex technical projects with a focus on customer success.
  • Strong interpersonal and communication skills; ability to thrive in dynamic, cross-functional teams.
Preferred Qualifications:
  • Master's degree in Computer Science, Engineering, or a related technical field.
  • Experience working in a startup or fast-paced environment.
  • Hands-on experience fine-tuning machine learning models, including supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF or RFT).
  • Solid understanding of generative AI, machine learning principles, and enterprise infrastructure.

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