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Entry Level Machine Learning Jobs in New York, NY

SynergisticIT

Backend Developer - Remote

Piscataway, NJ · On-site

$50.50 - $65.50/hr

Currently, We are looking for entry-level software programmers, Java Full stack developers, Python/Java developers, Data analysts/Data Engineers/ Data Scientists, Machine Learning engineers for ...

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Entry Level Machine Learning information

What types of projects can an entry level machine learning professional expect to work on in their first year?

As an entry-level machine learning professional, you’ll typically start by supporting more senior data scientists and engineers with tasks such as data cleaning, exploratory data analysis, and building baseline models. You may work on pilot projects like developing recommendation systems, automating simple classification tasks, or contributing to model evaluation and performance tuning. Collaboration with cross-functional teams—including software engineers, product managers, and domain experts—is common, providing valuable exposure to real-world business problems and laying a foundation for more complex responsibilities as you gain experience.

How to get into entry level machine learning with no experience?

Entry level machine learning roles typically require foundational knowledge in programming, statistics, and data analysis. Gaining skills through online courses, practicing with projects, and learning tools like Python, TensorFlow, or scikit-learn can help build a portfolio; internships or entry-level positions can provide practical experience.

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

To thrive as an Entry Level Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially in Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow or PyTorch, version control systems like Git, and data analysis libraries is commonly required. Strong problem-solving abilities, curiosity, and effective communication skills help differentiate candidates in collaborative and fast-evolving environments. These skills and qualifications are essential for building, testing, and improving machine learning models that drive innovation and business value.

What is the difference between Entry Level Machine Learning vs Data Analyst?

AspectEntry Level Machine LearningData Analyst
Required CredentialsBachelor's in CS, Math, or related; some knowledge of programming and statisticsBachelor's in Statistics, Math, or related; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentTech companies, startups, research labs; focus on developing models and algorithmsBusiness, finance, marketing; focus on interpreting data and generating reports
Employer & Industry UsageTech, e-commerce, healthcare; roles involve building predictive modelsRetail, finance, consulting; roles involve analyzing data trends and insights

Entry Level Machine Learning roles focus on developing algorithms and models using programming and statistical skills, often in tech-driven environments. Data Analysts interpret and visualize data to support business decisions, typically using tools like Excel and SQL. While both roles require analytical skills, Machine Learning positions emphasize coding and model development, whereas Data Analysts focus on data interpretation and reporting.

What are entry level machine learning jobs?

Entry-level machine learning jobs focus on creating and using software for the development of artificial intelligence (AI). In this role, you may help program computer software, engineer mechanical solutions, help develop learning objectives, and use analytics to determine whether or not the technology created is meeting development goals. Many entry-level machine learning jobs focus on particular parts of the industry. For example, some companies focus on surveillance and intelligence, while others are creating technology for self-driving vehicles. Employers often use this position as a type of extended learning period to help you develop your skills before you start taking responsibility for major projects.

More about Entry Level Machine Learning jobs
What are the most commonly searched types of Machine Learning jobs in New York, NY? The most popular types of Machine Learning jobs in New York, NY are:
What are popular job titles related to Entry Level Machine Learning jobs in New York, NY? For Entry Level Machine Learning jobs in New York, NY, the most frequently searched job titles are:
What job categories do people searching Entry Level Machine Learning jobs in New York, NY look for? The top searched job categories for Entry Level Machine Learning jobs in New York, NY are:
What cities near New York, NY are hiring for Entry Level Machine Learning jobs? Cities near New York, NY with the most Entry Level Machine Learning job openings:
Entry Level Machine Learning jobs near you
Infographic showing various Entry Level Machine Learning job openings in New York, NY as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 22% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

Machine Learning Developer

Elliot Partnership

New York, NY • On-site

Full-time

Re-posted 28 days ago

Job description

 OVERVIEW:
Machine learning developers work closely with researchers to creatively apply their knowledge of machine learning and software engineering to design, build, and maintain systems for high-performance, large-scale knowledge discovery in financial data. Machine learning developers have the opportunity to be part of an inclusive, collaborative, and engaging working environment.
WHAT YOU'LL DO DAY-TO-DAY:
Specific responsibilities include designing, implementing, testing, and documenting modules for all stages of the pipeline from data to predictions, assembling these modules into end-to-end systems, and interacting with researchers to achieve highly productive experimentation, model construction, and validation.
WHO WE'RE LOOKING FOR:
• Successful candidates will have a strong knowledge of software engineering, machine learning, and open-source machine learning ecosystems. A track record of building and applying high-performance machine learning systems is desired
• While an impressive record of academic achievement is a plus, we welcome outstanding candidates from diverse academic disciplines and backgrounds.

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