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Temporary Machine Learning Scientist Jobs in New Jersey

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Elizabeth, NJ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Paramus, NJ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Summit, NJ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Hoboken, NJ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Clifton, NJ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Paterson, NJ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

This role requires 1-2 years of experience in quantitative research, financial engineering, data science, or risk analytics within the securities industry. A background in machine learning ...

New

Machine Learning Tutor

Westfield, NJ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Trenton, NJ · Remote

$18 - $40/hr

... science roles and advanced AI coursework. * Conceptual Teaching & Problem-Solving: Skilled at ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

$40/hr

As a Machine Learning Engineering Intern, you will be part of a collaborative team supporting the ... Your primary role is to contribute to Workiva's data scientists' efforts within the Data Management ...

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Temporary Machine Learning Scientist information

What is a temporary machine learning scientist?

Temporary Machine Learning Scientists are professionals hired on a short-term basis to develop, implement, and optimize machine learning models within an organization. They typically work on specific projects or to fill a temporary gap in expertise, often collaborating with data scientists, engineers, and stakeholders. Their responsibilities may include data preprocessing, feature engineering, model selection, and evaluation. These roles are ideal for projects with defined timelines or exploratory research that does not require a permanent hire. Temporary contracts can range from a few months to a year, depending on the project's scope and needs.

What types of projects do temporary machine learning scientists typically work on, and how do they integrate with existing teams?

Temporary Machine Learning Scientists are often brought in to support short-term projects such as data analysis, model prototyping, or improving existing machine learning pipelines. Their work usually involves collaborating closely with data engineers, software developers, and product managers to ensure seamless integration of models into production systems. Since the role is temporary, effective communication and quick adaptation to the team's workflow are crucial. These scientists are expected to rapidly understand the company's data and objectives, deliver actionable insights, and document their work for team continuity after their contract ends.

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

To thrive as a Temporary Machine Learning Scientist, you typically need advanced knowledge of machine learning algorithms, data analysis, programming skills (such as Python or R), and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow, PyTorch, and tools for data processing and model deployment is often required, along with experience using cloud platforms such as AWS or Azure. Strong problem-solving abilities, adaptability, and effective communication skills help you quickly integrate into teams and deliver results on short-term projects. These skills ensure you can efficiently contribute to impactful solutions and adapt to rapidly changing project requirements.

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

AspectTemporary Machine Learning ScientistData Scientist
CredentialsTypically requires a master's or PhD in computer science, data science, or related fields; experience with machine learning frameworksUsually holds a bachelor's or master's in data science, statistics, or related fields; strong analytical skills
Work EnvironmentProject-based, often contract roles in tech, finance, or healthcare companiesFull-time or contract roles across various industries, focusing on data analysis and insights
Employer UsageHired for specialized machine learning projects, prototypes, or research tasksEngaged in data analysis, reporting, and building predictive models

In summary, a Temporary Machine Learning Scientist focuses on developing and implementing machine learning models on a temporary basis, often requiring advanced credentials and specialized skills. In contrast, a Data Scientist has a broader role in analyzing data and generating insights, with less emphasis solely on machine learning techniques.

What are popular job titles related to Temporary Machine Learning Scientist jobs in New Jersey?

For Temporary Machine Learning Scientist jobs in New Jersey, the most frequently searched job titles are:

What job categories do people searching Temporary Machine Learning Scientist jobs in New Jersey look for?

The top searched job categories for Temporary Machine Learning Scientist jobs in New Jersey are:

What cities in New Jersey are hiring for Temporary Machine Learning Scientist jobs?

Cities in New Jersey with the most Temporary Machine Learning Scientist job openings:

Full-time

Posted 4 days ago


Job description

Machine Learning Engineer

Newark, New Jersey, United States

Job Description

As a Machine Learning Engineer, you will play a pivotal role in driving the development and implementation of cutting-edge machine learning solutions for our client. Your responsibilities will encompass a wide range of tasks, from leading a small team of machine learning engineers to collaborating with cross-functional teams to deliver impactful solutions. You will be at the forefront of driving innovation and leveraging the power of machine learning to solve real-world problems, drive business growth, and create value.

Key Responsibilities

  • Lead and drive machine learning projects from inception to production: build relationships with business partners and cross-functional teams.
  • Collaborate with business leaders, subject matter experts, and decision-makers to develop success criteria and optimize new products, features, policies, and models.
  • Partner with data scientists to understand, implement, train, and design machine learning models.
  • Collaborate with the infrastructure team to improve the architecture, scalability, stability, and performance of ML platform.
  • Construct optimized data pipelines to feed machine learning models.
  • Extend existing machine learning libraries and frameworks.
  • Develop processes, model monitoring, and governance framework for successful ML model operationalization.
  • Define objectives for the Machine Learning platform, own the technical roadmap, and be accountable for delivering results.
  • Define standards for engineering and operational excellence for running best-in-class ML platforms and continue to improve ML platforms to keep up with the latest innovations.
  • Design and implement the best architectural practices in the delivery of data science use cases.

Key Skills/Knowledge/Experience

  • 7+ years of experience in Machine Learning.
  • Extensive software engineering experience with strong working experience as a Machine Learning Engineer.
  • Bachelor's degree in computer science, computer engineering, or a related engineering field. Masters degree preferred.
  • Advanced proficiency with Python, Java, and Scala.
  • Strong computer science fundamentals such as algorithms, data structures, multithreading.
  • Experience working with Generative AI, using LangChain for Gen AI and techniques like RAG.
  • Experience using ML and DL Libraries:XGBoost, SKlearn, Tensorflow or PyTorch
  • In-depth experience building solutions using public clouds such as AWS, GCP.
  • Experience using ML platforms like SageMaker, H2O, DataRobot, etc.
  • Strong knowledge on ML model development life cycle components like containers, batch vs real time inference endpoints, application security testing etc.
  • Experience managing relationships in a cross-functional environment with multiple stakeholders.
  • Experience with developing and deploying production-grade applications with ML inferences using automation pipeline on cloud.
  • Experience working in Agile/ Scrum development process.
  • Thought leadership and innovative thinking.
  • Excellent communication and collaboration skills.

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