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Machine Learning Algorithms Jobs in Princeton, NJ

AI Scientist

New York, NY · Hybrid

$150K - $200K/yr

Implement state of the art machine learning algorithms * Design deep learning architectures. * Develop model frameworks for investment professionals * Collaborate with portfolio managers and ...

Develop machine learning models for geospatial inference of key ecosystem metrics, leveraging ... Develop and refine advanced deep generative models and reinforcement learning algorithms for built ...

Machine Learning Engineer

New York, NY · On-site

$85K - $125K/yr

Kitware is a leader in advanced research and algorithm development in artificial intelligence (AI ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

Familiar with machine learning curricula and common challenges such as understanding bias-variance tradeoff, selecting appropriate algorithms for problem types, and interpreting model performance ...

Familiar with machine learning curricula and common challenges such as understanding bias-variance tradeoff, selecting appropriate algorithms for problem types, and interpreting model performance ...

Familiar with machine learning curricula and common challenges such as understanding bias-variance tradeoff, selecting appropriate algorithms for problem types, and interpreting model performance ...

Design, build, and deploy scalable machine learning models to enhance product features, optimize performance, and drive intelligent automation. * Algorithm Optimization : Fine-tune and optimize ...

AI Scientist

New York, NY · On-site

$150K - $200K/yr

Implement state of the art machine learning algorithms * Design deep learning architectures. * Develop model frameworks for investment professionals * Collaborate with portfolio managers and ...

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Machine Learning Algorithms information

See Princeton, NJ salary details

$26.7K

$44.6K

$92.2K

How much do machine learning algorithms jobs pay per year?

As of Jun 19, 2026, the average yearly pay for machine learning algorithms in Princeton, NJ is $44,639.00, according to ZipRecruiter salary data. Most workers in this role earn between $34,100.00 and $48,200.00 per year, depending on experience, location, and employer.

What are machine learning algorithms?

Machine learning algorithms are computational methods that enable computers to learn patterns and make decisions or predictions from data without being explicitly programmed for each task. These algorithms can be classified into categories such as supervised learning, unsupervised learning, and reinforcement learning, each suited for different data and goals. Examples include decision trees, support vector machines, neural networks, and clustering algorithms. The choice of algorithm depends on the type of problem, the nature of the data, and the desired outcome.

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

To excel as a Machine Learning Algorithms Engineer, you need a solid background in mathematics, statistics, programming (especially Python or R), and a relevant degree in computer science or a related field. Familiarity with machine learning frameworks (like TensorFlow, PyTorch, or scikit-learn), data preprocessing tools, and cloud platforms is typically required, along with knowledge of version control systems. Strong analytical thinking, problem-solving abilities, and effective communication skills set top performers apart in this role. These skills and qualities are critical for designing robust models, collaborating with cross-functional teams, and translating complex data into actionable solutions.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or at large tech companies can earn salaries of $500,000 or more, including base pay, bonuses, and stock options. Achieving this level typically requires a strong educational background, specialized certifications, and a track record of successful projects.

Which 3 jobs will survive AI?

Machine learning engineers, data scientists, and AI specialists are likely to continue thriving as AI advances because they develop, interpret, and improve AI systems. These roles require specialized skills in programming, statistical analysis, and domain expertise that are difficult to fully automate. Continuous learning and staying updated with new tools like TensorFlow or PyTorch are essential for these jobs.

What is the difference between Machine Learning Algorithms vs Data Scientists?

AspectMachine Learning AlgorithmsData Scientists
CredentialsKnowledge of algorithms, programming, statisticsAdvanced degrees in data science, statistics, or related fields
Work EnvironmentDeveloping, testing, and tuning algorithmsAnalyzing data, building models, interpreting results
Industry UsageEmbedded within data science workflows and toolsLeading data analysis projects, decision-making

While machine learning algorithms are the core tools used by data scientists, the role of a data scientist encompasses understanding, applying, and interpreting these algorithms within broader data analysis and business contexts. Machine learning algorithms are technical components, whereas data scientists integrate these tools to derive insights and inform strategies.

Is ML a high paying job?

Machine Learning (ML) jobs are generally well-paid due to the specialized skills required, such as programming, data analysis, and knowledge of algorithms. Salaries vary based on experience, location, and industry, but many ML roles offer competitive compensation compared to other tech positions.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or chief AI officers, often requiring advanced skills in algorithms, data science, and deep learning. These positions usually involve leadership responsibilities, extensive experience, and may be located in competitive tech hubs or large organizations with substantial AI investments.

What are some common challenges faced when collaborating with cross-functional teams as a Machine Learning Algorithms specialist?

As a Machine Learning Algorithms specialist, collaborating with cross-functional teams such as data engineers, software developers, and product managers can present challenges like aligning on project goals, communicating complex technical concepts to non-experts, and integrating models into existing systems. It's important to establish clear communication channels, define shared objectives early, and actively participate in iterative feedback cycles. These practices help ensure that machine learning solutions are both technically sound and aligned with business needs.
What are popular job titles related to Machine Learning Algorithms jobs in Princeton, NJ? For Machine Learning Algorithms jobs in Princeton, NJ, the most frequently searched job titles are:
What job categories do people searching Machine Learning Algorithms jobs in Princeton, NJ look for? The top searched job categories for Machine Learning Algorithms jobs in Princeton, NJ are:
Software Engineer II - Machine Learning, Marketplace/Maps/Membership/AV

Software Engineer II - Machine Learning, Marketplace/Maps/Membership/AV

Uber

New York, NY • On-site

Other

Retirement

Posted 6 days ago


Uber rating

6.9

Company rating: 6.9 out of 10

Based on 105 frontline employees who took The Breakroom Quiz

4th of 9 rated taxi private hire


Job description

About the RoleCollaborates with stakeholders to design, develop, optimize, and productionize machine learning (ML) or ML-based solutions and systems that are used within a team to solve moderately complex problems.About the Team(We are hiring for multiple teams)We are building the future of Uber's mobility and logistics platforms. As a software engineer, you will contribute to high-scale, strategically critical systems that impact millions of users and redefine the global transportation and membership landscape.Our teams drive innovation across critical areas including:- Maps & Routing: Building the core technologies for location accuracy, sensor data processing, and state-of-the-art routing algorithms to power ETAs, navigation, and matching for all Uber products.- Uber One Membership: Enhancing user experience and growth for Uber One, a fast-growing program providing members with exclusive benefits, best prices, and priority across the platform.- Delivery Marketplace: Delivery Marketplace is a central pillar of Uber's delivery products, serving as the "brain" of the operation. We drive every decision that enables orders to go from point A to point B - from Uber Eats & Grocery, to newer verticals like Uber Direct and Connect

We're responsible for everything: from dispatch decisions, predicting food ready time, delivery times, and optimizing pickup times, to ensuring we deliver the most efficient and impactful solutions for Uber's most critical business goals- Autonomous Mobility & Delivery (AM&D): Pioneering the integration of autonomous vehicles into the existing ecosystem, tackling the complex challenge of building a reliable, efficient, and scalable hybrid marketplace for both Rides and Eats.What You'll Do- Design, build, and deploy scalable machine learning models to production to solve real-world business problems.- Collaborate with cross-engineering teams, data scientists and other partners to gather requirements and translate them into technical specification- Write clean, testable, and efficient code to ensure models run with low latency and high reliability.- Implement monitoring systems to track model performance, stability, and data drift in live environments.- Stay up-to-date with standard machine learning algorithms and industry trends to continuously improve our tech stack.## Basic Qualifications:- Bachelor's degree or equivalent in Machine Learning, AI, Data Science, Computer Science, Engineering, Mathematics or related field with at least 1 year of full-time Machine Learning work experience OR PhD in Machine Learning, AI, Data Science, Computer Science, Engineering, Mathematics or related field- Proficiency in at least one programming language such as Java, C++, Python, or Go- 1 year of experience with ML algorithms/modeling- developing, training, productionization and monitoring of ML solutions at scale.## Preferred Qualifications:- Master's degree or higher in Machine Learning, AI, Data Science, Computer Science, Engineering, Mathematics or related field.- More than 3 years of full-time machine learning work experience- Experience with the full ML lifecycle (at Uber Scale), including model deployment, containerization and workflow orchestration.- Experience in translating ambiguous business problems into technical solutions in a structured and principled way.- Strong communication skills, including through documentation and design discussions- Experience with optimization techniques and algorithmic development- Strong problem-solving skills, with expertise in algorithms, data structures, and complexity analysis- High bar for quality as demonstrated by code reviews, documentation, unit and integration testingFor New York, NY-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year.For San Francisco, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year.For Seattle, WA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year.For Sunnyvale, CA-based roles: The base salary range for this role is USD$171,000 per year - USD$190,000 per year.For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits

More details can be found at the following link [https://jobs.uber.com/en/benefits](https://jobs.uber.com/en/benefits).Uber's mission is to reimagine the way the world moves for the better. Here, bold ideas create real-world impact, challenges drive growth, and speed fuels progress. What moves us, moves the world - let's move it forward, together.Uber is proud to be an Equal Opportunity employer

All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing [this form](https://forms.gle/aDWTk9k6xtMU25Y5A).Offices continue to be central to collaboration and Uber's cultural identity

Unless formally approved to work fully remotely, Uber expects employees to spend at least half of their work time in their assigned office. For certain roles, such as those based at green-light hubs, employees are expected to be in-office for 100% of their time. Please speak with your recruiter to better understand in-office expectations for this role.


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