ZipRecruiter

Log In

2

Full Time Machine Learning Engineer New Grad Jobs in New York

Hang

Machine Learning Engineer

New York, NY · On-site +1

Stay up-to-date with the latest developments in machine learning and AI, and explore new techniques ... Strong programming skills in Python and familiarity with ML frameworks (like TensorFlow or PyTorch)

Goodfire

Machine Learning Engineer

Manhattan, NY · On-site

They are seeking Machine Learning Engineers to contribute to their platform for training ... new machine learning workflows and pipelines into our product and deploy to customers. • Ensure ...

Point72

Machine Learning Engineer

New York, NY · On-site

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 ...

Treeswift Inc

Machine Learning Engineer

New York, NY · On-site

... new construction, and accelerate recovery from severe storms. After starting our work with ... This is a full-time, hybrid/2-day a week in person role in our NYC office. Key Responsibilities

DraftKings, Inc.

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

It's transforming how we enhance customer experiences, streamline operations, and unlock new ... The US base salary range for this full-time position is 134,400.00 USD - 168,000.00 USD, plus bonus ...

next page

Showing results 1-20

All JobsFull Time Machine Learning Engineer New Grad JobsFull Time Machine Learning Engineer New Grad Jobs in New York

Full Time Machine Learning Engineer New Grad information

What does a Full Time Machine Learning Engineer New Grad do?

A Full Time Machine Learning Engineer New Grad is an entry-level professional who designs, builds, and deploys machine learning models as part of a technical team. They often work on tasks such as data preprocessing, developing and testing algorithms, and integrating models into production systems. New grad engineers usually collaborate with data scientists, software engineers, and product teams to solve real-world problems using machine learning. Their responsibilities also include staying updated with the latest advancements in the field and learning best practices for model development and deployment.

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

To excel as a Full Time Machine Learning Engineer New Grad, you typically need a solid background in computer science, statistics, and mathematics, often demonstrated through a relevant degree or coursework. Familiarity with programming languages like Python, and experience with machine learning libraries such as TensorFlow or PyTorch, as well as tools for data analysis and version control, are essential. Strong problem-solving abilities, effective communication, and a willingness to learn new technologies help new grads stand out in collaborative and fast-paced environments. These skills and qualities are crucial for building effective models, working well within teams, and adapting to the rapidly evolving field of machine learning.

What are some common challenges new graduates face when transitioning into a full-time Machine Learning Engineer role?

New graduates entering a full-time Machine Learning Engineer position often encounter challenges such as adapting to large-scale production systems, collaborating with cross-functional teams, and bridging the gap between academic projects and real-world business problems. Unlike school assignments, industry projects require scalable, maintainable code and thorough documentation. Additionally, new grads must quickly learn to communicate their technical findings to non-technical stakeholders and prioritize tasks amid fast-paced development cycles.

What is the difference between Full Time Machine Learning Engineer New Grad vs Data Scientist New Grad?

AspectFull Time Machine Learning Engineer New GradData Scientist New Grad
Required CredentialsBachelor's in CS, Math, or related; some internshipsBachelor's in Statistics, CS, or related; some internships
Work EnvironmentDeveloping ML models, deploying algorithms, coding in Python/C++Analyzing data, creating reports, statistical modeling
Industry UsageTech, finance, healthcare, focusing on ML systemsTech, marketing, finance, focusing on data analysis

Full Time Machine Learning Engineer New Grad roles focus on building and deploying machine learning models, requiring coding and engineering skills. Data Scientist New Grad roles emphasize data analysis, statistical modeling, and insights. Both roles often share similar educational backgrounds but differ in daily tasks and technical focus.

What are the most commonly searched types of Machine Learning Engineer New Grad jobs in New York? The most popular types of Machine Learning Engineer New Grad jobs in New York are:
What are popular job titles related to Full Time Machine Learning Engineer New Grad jobs in New York? For Full Time Machine Learning Engineer New Grad jobs in New York, the most frequently searched job titles are:
What job categories do people searching Full Time Machine Learning Engineer New Grad jobs in New York look for? The top searched job categories for Full Time Machine Learning Engineer New Grad jobs in New York are:
Full Time Machine Learning Engineer New Grad jobs near you
Infographic showing various Full Time Machine Learning Engineer New Grad job openings in New York as of June 2026, with employment types broken down into 99% Full Time, and 1% Part Time. Highlights an 91% Physical, 2% Hybrid, and 7% Remote job distribution.

Machine Learning Engineer

Purple Drive Technologies

Newark, NJ • On-site

Full-time

Retirement

Posted 16 days ago

Job description

Overview:
Role: Machine Learning Engineer
As a Machine Learning Engineer, you will play a critical role in designing, developing, and deploying advanced machine learning solutions that drive innovation and create measurable business value. You will collaborate closely with business stakeholders, data scientists, and cross-functional engineering teams to transform ideas into scalable, production-ready systems. This role requires both strong technical expertise and leadership ability to guide a small team and deliver impactful solutions.
Key Responsibilities
  • Lead and deliver machine learning projects from inception through production, building strong relationships with business partners and cross-functional teams.
  • Collaborate with business leaders and subject matter experts to define success criteria and optimize products, features, and models.
  • Partner with data scientists to design, implement, and train machine learning models.
  • Work with infrastructure teams to enhance architecture, scalability, stability, and performance of ML platforms.
  • Design and optimize data pipelines to support high-performance ML model training and inference.
  • Extend and customize machine learning libraries and frameworks for project-specific needs.
  • Define and implement model monitoring, governance, and operationalization processes for ML solutions.
  • Establish objectives and own the technical roadmap for ML platforms, ensuring delivery of results.
  • Define and promote standards of engineering and operational excellence for ML systems.
  • Apply architectural best practices in the delivery of data science and AI solutions.
Required Skills & Experience
  • Strong background in software engineering with proven experience as a Machine Learning Engineer.
  • Bachelor's degree in Computer Science, Computer Engineering, or related field; Master's preferred.
  • Advanced proficiency in Python, Java, and Scala with solid CS fundamentals (algorithms, data structures, multithreading).
  • Hands-on experience with Generative AI, LangChain, and RAG-based techniques.
  • Expertise in ML/DL libraries such as XGBoost, Scikit-learn, TensorFlow, and PyTorch.
  • Experience building and deploying ML solutions on public clouds (AWS, GCP).
  • Familiarity with ML platforms such as SageMaker, H2O, and DataRobot.
  • Strong knowledge of the ML lifecycle, including containerization, batch vs. real-time inference, and application security.
  • Proven track record in developing and deploying production-grade ML applications with cloud-based automation pipelines.
  • Experience working in Agile/Scrum environments with multiple stakeholders.
  • Excellent communication, collaboration, and problem-solving skills with thought leadership and innovative thinking.
Nice-to-Have
  • Experience with search platforms (e.g., Solr, Elasticsearch).
  • Hands-on experience building recommender systems.
  • Exposure to graph databases (e.g., Neo4j).
  • Familiarity with CI/CD tools (e.g., Jenkins).
  • Domain knowledge in Financial Services, Insurance, or 401K.
  • AWS Solutions Architect certification.

Apply