Machine Learning Engineer Jobs in New York
New York City stands as a premier destination for machine learning engineers, boasting a vibrant tech ecosystem and a plethora of career opportunities across various industries. This bustling metropolis offers a competitive landscape for professionals seeking to innovate and excel in machine learning. Companies from startups to tech giants in NYC are on the lookout for skilled engineers to leverage data for strategic insights and enhanced decision-making.
Companies Hiring Machine Learning Engineers
Here’s a list of companies hiring machine learning engineers in New York :
1. Google
Requirements:
- Proficiency in Python, C++, or Java.
- Experience with TensorFlow, PyTorch, or similar.
- Strong understanding of statistical analysis.
Career Page
2. Facebook (Meta)
Requirements:
- Advanced degree in Computer Science or related field.
- Deep understanding of machine learning frameworks.
- Expertise in implementing deep learning algorithms.
Career Page
3. Amazon
Requirements:
- Experience in designing and deploying large-scale machine learning models.
- Programming skills in Python or Java.
- Familiarity with distributed computing frameworks.
Career Page
4. IBM
Requirements:
- Background in machine learning, data science, or AI.
- Experience with cloud platforms like AWS or Azure.
- Strong problem-solving and analytical skills.
Career Page
5. Microsoft
Requirements:
- Proven experience with machine learning models and data pipelines.
- Fluency in programming languages like Python, C++, or Java.
- Familiarity with Azure and other Microsoft technologies.
Career Page
6. Goldman Sachs
Requirements:
- Background in financial analytics and machine learning.
- Proficiency in R, Python, and SQL.
- Deep understanding of machine learning model deployment.
Career Page
7. JPMorgan Chase & Co.
Requirements:
- Knowledge of machine learning techniques applied to financial services.
- Expertise in Python or Scala.
- Experience working with big data technologies like Hadoop or Spark.
Career Page
8. Bloomberg LP
Requirements:
- Master’s or PhD in Computer Science or related field.
- Experience with machine learning frameworks and financial data.
- Programming skills in Python or C++.
Career Page
9. Spotify
Requirements:
- Understanding of recommendation systems and user data analysis.
- Proficiency in Python, Java, or SQL.
- Familiarity with distributed computing systems.
Career Page
10. Etsy
Requirements:
- Experience in building and deploying machine learning models.
- Strong programming skills in Python or Java.
- Knowledge of data science and statistical analysis.
Career Page
11. Uber
Requirements:
- Advanced degree in Computer Science or relevant field.
- Proven experience in machine learning and data modeling.
- Proficiency in Python or C++.
Career Page
12. Netflix
Requirements:
- Solid understanding of machine learning algorithms and video analytics.
- Expertise in programming languages like Python, C++, or Java.
- Familiarity with cloud computing and data pipelines.
Career Page
13. LinkedIn
Requirements:
- Strong background in machine learning, statistics, and data science.
- Experience with Hadoop, Spark, or other big data frameworks.
- Programming skills in Python or Java.
Career Page
14. IBM Watson
Requirements:
- Proficiency in natural language processing and machine learning models.
- Experience with Python or R.
- Background in cognitive computing and analytics.
Career Page
15. WeWork
Requirements:
- Deep understanding of machine learning algorithms and business analytics.
- Expertise in Python or R.
- Experience with cloud platforms and data visualization tools.
Career Page
16. Twitter
Requirements:
- Strong understanding of machine learning models applied to social data.
- Programming skills in Python, Java, or Scala.
- Familiarity with data visualization and analytics platforms.
Career Page
17. Palantir Technologies
Requirements:
- Experience in data science, machine learning, or AI.
- Proficiency in Python, Java, or C++.
- Deep knowledge of statistical analysis and big data platforms.
Career Page
18. Capital One
Requirements:
- Advanced degree in Computer Science or relevant field.
- Proficiency in machine learning frameworks and data analytics.
- Programming skills in Python or Scala.
Career Page
19. Accenture
Requirements:
- Background in machine learning models and cloud platforms.
- Programming skills in Python, Java, or R.
- Understanding of data visualization and business analytics.
Career Page
20. Salesforce
Requirements:
- Strong understanding of machine learning algorithms and software development.
- Experience with Python, R, or Java.
- Familiarity with cloud computing platforms and data pipelines.
Career Page
21. Databricks
Requirements:
- Knowledge of machine learning frameworks like TensorFlow or PyTorch.
- Programming proficiency in Python or Scala.
- Understanding of distributed computing frameworks.
Career Page
22. Dropbox
Requirements:
- Advanced degree in Computer Science or related field.
- Expertise in machine learning models and cloud platforms.
- Programming skills in Python, R, or Java.
Career Page
23. Airbnb
Requirements:
- Proficiency in machine learning algorithms and data analysis.
- Programming expertise in Python or C++.
- Familiarity with big data frameworks like Hadoop or Spark.
Career Page
24. Squarespace
Requirements:
- Deep knowledge of machine learning models and data science.
- Programming skills in Python or Java.
- Experience in building and deploying large-scale data models.
Career Page
25. Spotify
Requirements:
- Background in recommendation systems and machine learning algorithms.
- Programming expertise in Python, Java, or SQL.
- Familiarity with data visualization and distributed computing systems.
Career Page
Job Portals
You can find machine learning engineer jobs through these portals:
- LinkedIn Jobs
- Indeed
- Glassdoor
- Dice
- SimplyHired
Salary of Machine Learning Engineer
The salary of a Machine Learning Engineer varies widely depending on factors like geographical location, level of experience, education, and the specific industry. In general, in the United States, entry-level machine learning engineers can expect to earn between $80,000 and $100,000 annually. Mid-level engineers with 3 to 5 years of experience often see salaries ranging from $110,000 to $140,000, while senior-level engineers with over five years of experience can earn between $140,000 and $180,000 or more per year.
In tech hubs such as San Francisco and New York, salaries can be on the higher end due to the concentration of high-tech companies and the cost of living. Additionally, engineers working in industries like finance or pharmaceuticals may command higher wages due to the critical nature of their work. Bonuses, stock options, and other incentives can also significantly boost total compensation in this field.
Experience-Wise Salary Trend
| Salary Range | |
|---|---|
| Entry-Level (0-2 years) | $80,000 – $100,000 |
| Mid-Level (3-5 years) | $110,000 – $140,000 |
| Senior-Level (5+ years) | $140,000 – $180,000 |
FAQs
Do I need a Ph.D. to be a Machine Learning Engineer?
While a Ph.D. is not strictly necessary, many employers value it, especially for more complex roles. However, a Master’s or Bachelor’s degree in Computer Science or a related field can be sufficient if accompanied by relevant experience and skills in machine learning.
What programming languages are essential for a Machine Learning Engineer?
Python is the most crucial language due to its extensive libraries and frameworks like TensorFlow and PyTorch. Knowledge of other programming languages such as R, Java, and C++ can also be beneficial.
Which machine learning frameworks should I be familiar with?
Aspiring machine learning engineers should aim to master frameworks such as TensorFlow, PyTorch, Keras, and Scikit-learn. These tools are essential for building and deploying machine learning models efficiently.
How much experience is needed for an entry-level position?
Entry-level machine learning positions typically require some practical knowledge, which can be gained through internships, academic projects, or personal projects. Demonstrating hands-on experience with real-world data and machine learning algorithms is key.
What can I do to improve my chances of getting hired as a Machine Learning Engineer?
Building a robust portfolio of projects, contributing to open-source projects, networking within the tech community, and staying updated with the latest technologies and advancements in machine learning will significantly enhance your employability. Certifications in relevant technologies can also add value to your resume.