1

Graduate Machine Learning Engineer Jobs in New York

Machine Learning Engineer

Manhattan, NY · On-site +1

$180K - $280K/yr

Machine Learning Engineer Legal work is buried in unstructured documents, repetitive workflows, and data that no existing system handles well -- and we're building the AI to fix it. As a Machine ...

Machine Learning Engineer New York, NY | Full Time COMPENSATION RANGE: 140,000.00 - 170,000.00 (On Target Earnings) The Role: As a Machine Learning Senior Engineer you will be part of all the major ...

Machine Learning Engineer (GCP)

Manhattan, NY · Remote

$58.25 - $79.75/hr

Machine Learning Engineer- 2 Positions Overall experience of minimum 7 years and machine learning experience of at least 3 - 4 years. Location- Remote Overview: As a GCP ML Engineer, you'll design ...

Machine Learning Engineer

Manhattan, NY · Remote

$154K/yr

Machine Learning Engineer (AI Data Trainer) About the Role What if your machine learning expertise could directly influence how the world's most advanced AI systems reason, plan, and solve problems ...

Machine Learning Engineer

New York, NY · Hybrid

$90K - $254K/yr

We are in search of an exceptional Machine Learning Engineer to join our accomplished team. In this role, you will take the lead in developing and fine-tuning predictive ML models, with a primary ...

Machine Learning Engineer

New York, NY · On-site +1

$148K - $212K/yr

We are looking for a Machine Learning Engineer to join the Personalization (PZN) team - an area of hardworking engineers that are passionate about understanding what drives user satisfaction with ...

Machine Learning Engineer

New York, NY · On-site

$148K - $212K/yr

We are looking for a Machine Learning Engineer to join the Personalization (PZN) team - an area of hardworking engineers that are passionate about understanding what drives user satisfaction with ...

Treeswift is seeking a highly skilled and motivated engineer to join our team. You will play a pivotal role in developing and deploying state-of-the-art machine learning solutions to advance our ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

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. You ...

Treeswift is seeking a highly skilled and motivated engineer to join our team. You will play a pivotal role in developing and deploying state-of-the-art machine learning solutions to advance our ...

Lead Machine Learning Engineer

Manhattan, NY · On-site +1

$112K - $148K/yr

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. You ...

Lead Machine Learning Engineer

New York, NY · On-site +1

$112K - $147K/yr

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. You ...

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 ...

Lead Machine Learning Engineer

New York, NY · On-site

$112K - $147K/yr

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. You ...

next page

Showing results 1-20

Graduate Machine Learning Engineer information

See New York salary details

$34.5K

$140.9K

$211.7K

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

As of Jun 9, 2026, the average yearly pay for graduate machine learning engineer in New York is $140,878.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,000.00 and $169,600.00 per year, depending on experience, location, and employer.

What does a Graduate Machine Learning Engineer do?

A Graduate Machine Learning Engineer is an entry-level professional who designs, develops, and tests machine learning models and algorithms. They work with data scientists and engineers to preprocess data, train models, and deploy solutions to solve real-world problems. Their responsibilities often include coding in languages like Python, using libraries such as TensorFlow or PyTorch, and staying updated with the latest advancements in machine learning. This role serves as a starting point for a career in AI, providing hands-on experience in building and optimizing intelligent systems.

What are the key skills and qualifications needed to thrive as a Graduate Machine Learning Engineer, and why are they important?

To thrive as a Graduate Machine Learning Engineer, you need a solid foundation in computer science, mathematics (especially statistics and linear algebra), and proficiency in programming languages like Python, often supported by a relevant degree. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), version control systems (like Git), and experience with cloud platforms or data management tools are typically expected. Strong analytical thinking, problem-solving abilities, and effective communication help you collaborate and translate complex concepts into practical solutions. These skills and qualities are crucial for developing robust models, integrating them into real-world applications, and contributing effectively to multidisciplinary teams.

What are some common challenges faced by Graduate Machine Learning Engineers during their first year, and how can they overcome them?

Graduate Machine Learning Engineers often encounter challenges such as bridging the gap between academic knowledge and real-world application, working with large or messy datasets, and learning to collaborate within cross-functional teams. Adapting to production-level code standards and understanding existing codebases can also be demanding. To overcome these hurdles, it's helpful to seek mentorship from experienced colleagues, actively participate in code reviews, and invest time in learning best practices for data preprocessing and model deployment. Embracing continuous learning and open communication will ease the transition into the professional environment.

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

AspectGraduate Machine Learning EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related field; some internshipsBachelor's or Master's in Statistics, Data Science, or related field; often with experience
Work EnvironmentDeveloping ML models, coding, testing algorithmsAnalyzing data, creating visualizations, deriving insights
Employer & Industry UsageTech companies, startups, research labsFinance, healthcare, tech, consulting firms

While both roles involve working with data and algorithms, Graduate Machine Learning Engineers focus on developing and deploying machine learning models, often requiring coding and technical skills. Data Scientists analyze data to extract insights and inform decisions. The roles overlap in skills but differ in primary responsibilities and focus areas.

Machine Learning Engineer

Machine Learning Engineer

Exaways Corporation

Berkeley Heights, NJ • On-site

Other

Posted 19 days ago


Job description

Job Description Summary:
• Machine Learning Ops Engineer to build & support scalable, highly available and robust Machine Learning (ML) /Deep Learning (DL) platform using ML/DL frameworks, High-Performance Computing (HPC) machines, Data Science tools, products & services in cloud and on-premises for client's data & analytics organization.
• Role will expose you to cutting edge technologies related to ML/DL and the ideal candidate will be driven, focused and enthusiastic about learning new technologies and implement them.
Responsibilities:
• Build, install, configure, manage, and scale state-of-the-art machine learning platform in cloud (Azure preferred) & on-premises powering client's Data & Analytics products and solutions.
• Work with data scientists, architects, DevOps engineers, and vendors to implement scalable ML/DL solutions in cloud and on-premises to solve complex problems.
• Creating & maintaining ML/DL pipelines and overall ML/DL workflow orchestration including but not limited to data collection, prep, transform, analyze, experiment, train, validate, serve, monitor, etc.
• Implement ML/DL solutions addressing performance, scalability, and the governance/ traceability of machine learning models
• Iterate quickly through latest technologies, products, frameworks, and R&D on latest information related to ML/DL frameworks, tools & services.
Qualifications:
• 4+ years' experience delivering DevOps and MLOps in a Production/Enterprise setting
• Bachelor's degree required; Masters preferred in Computer Science or Data Science
• Excellent written and oral communication and presentation skills.
• Experienced in a technical role involving platform and infrastructure operation.
• System administration experience of Unix or Linux systems.
• Container-based deployment experience using Docker and Kubernetes.
• Proficient with the machine learning modelling lifecycle and comfortable addressing both functional and technical aspects of model delivery
• Experience with managing, deployment of large distributed systems like Spark, DASK & H20 and heterogenous platform components.
• Experienced with programming languages like Python or R and comfortable in understanding statistical foundations of most used ML algorithms.
• Experienced with Machine Learning frameworks: Sci-kit, Keras, Theano, TensorFlow, Spark Mllib, etc.
• Preferred hand-on experience IBM Watson Machine Learning systems or related preferred
• Preferred hands-on experience with HPC - Nvidia, CUDA
• Preferred experience with configuration Management tools like Ansible, puppet
• Preferred experience in monitoring and performance analysis of Machine Learning platforms using tools like Grafana and Zabbix.