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Internship Edge Ai Machine Learning Jobs in New York

Fireworks AI

Applied Machine Learning Engineer

New York, NY · On-site

$170K - $240K/yr

As an Applied Machine Learning Engineer, you will serve as a vital bridge between cutting-edge AI research and practical, real-world applications. Your work will focus on developing, fine-tuning, and ...

1Kosmos

AI / Machine Learning Engineer

Iselin, NJ · On-site

We are looking for an AI / Machine Learning Engineer to design, build, and deploy advanced computer ... Benefits * Cutting-Edge Tech Stack: Build with decentralized identity protocols, FedRamp High ...

1Kosmos

AI / Machine Learning Engineer

Iselin, NJ · On-site

We are looking for an AI / Machine Learning Engineer to design, build, and deploy advanced computer ... Benefits * Cutting-Edge Tech Stack: Build with decentralized identity protocols, FedRamp High ...

Chefman

Machine Learning Engineer

Mahwah, NJ · On-site

This is an opportunity to work at the intersection of machine learning, embedded systems, computer vision, and smart consumer technology, bringing cutting-edge AI from research into products used by ...

1Kosmos

AI / Machine Learning Engineer

Iselin, NJ · Hybrid

We are looking for an AI / Machine Learning Engineer to design, build, and deploy advanced computer ... Benefits * Cutting-Edge Tech Stack: Build with decentralized identity protocols, FedRamp High ...

Everest

AI / Machine Learning Engineering Lead

Warren, NJ · Hybrid

$180K - $220K/yr

AI / Machine Learning Engineering Lead Company: Everest Reinsurance Company Job Category: Technology About Everest: Everest is a global leader in risk management, rooted in a rich, 50+ year heritage ...

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Internship Edge Ai Machine Learning information

What is an internship edge AI machine learning?

Internship Edge AI Machine Learning positions are entry-level roles designed for students or recent graduates who want hands-on experience working with artificial intelligence and machine learning technologies, especially those related to 'edge' computing. These internships focus on developing, optimizing, and deploying AI/ML models that run on edge devices such as smartphones, IoT devices, and embedded systems, rather than in the cloud. Interns typically assist in research, data preparation, model training, and software development while gaining industry-relevant skills. These roles are ideal for individuals interested in both hardware and software aspects of AI. The experience gained can be valuable for future careers in data science, machine learning engineering, or AI research.

What types of projects can I expect to work on during an internship in edge AI and machine learning?

As an intern in Edge AI and Machine Learning, you will likely work on projects that involve developing and optimizing machine learning models for deployment on edge devices such as smartphones, IoT sensors, or embedded systems. Typical tasks include data preprocessing, model training and evaluation, and implementing algorithms with resource constraints in mind. You may also collaborate with hardware engineers and software developers to ensure that your solutions run efficiently on limited hardware. This hands-on experience provides a strong foundation for understanding real-world AI deployment challenges and can open doors to more advanced roles in the future.

What are the key skills and qualifications needed to thrive as an internship edge AI machine learning professional, and why are they important?

To thrive in an Internship Edge AI Machine Learning role, you need a solid background in computer science, mathematics, and machine learning concepts, typically supported by coursework or relevant projects. Familiarity with programming languages like Python, machine learning libraries (such as TensorFlow or PyTorch), and cloud or edge computing platforms is highly valuable. Strong analytical thinking, problem-solving abilities, and effective teamwork skills help you adapt and contribute meaningfully in collaborative research and development environments. These competencies are crucial for innovating and deploying machine learning models on edge devices, ensuring impactful real-world AI solutions.

What is the difference between Internship Edge Ai Machine Learning vs Data Analyst?

AspectInternship Edge Ai Machine LearningData Analyst
Required CredentialsRelevant coursework, basic programming skills, possibly some certificationsDegree in statistics, mathematics, or related field; proficiency in data tools
Work EnvironmentInternship setting, collaborative teams, research-focusedOffice environment, data-driven decision-making teams
Employer & Industry UsageTech companies, startups, research institutionsBusiness, finance, healthcare, marketing sectors

Internship Edge Ai Machine Learning roles typically focus on foundational skills in AI and machine learning, often as entry-level or internship positions. Data Analysts work across various industries analyzing data to inform business decisions. While both roles involve working with data, AI internships emphasize machine learning models, whereas Data Analysts focus on data interpretation and reporting.

What are the most commonly searched types of Edge Ai Machine Learning jobs in New York?

The most popular types of Edge Ai Machine Learning jobs in New York are:

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Internship Edge Ai Machine Learning jobs near you

Applied Machine Learning Engineer

Fireworks AI

New York, NY • On-site

$170K - $240K/yr

Full-time

Re-posted 16 days ago

Job description

About Us:
Fireworks is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, Fireworks powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, Fireworks is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI.
The Role:
As an Applied Machine Learning Engineer, you will serve as a vital bridge between cutting-edge AI research and practical, real-world applications. Your work will focus on developing, fine-tuning, and operationalizing machine learning models that drive business value and enhance user experiences. This is a hands-on engineering role that combines deep technical expertise with a strong customer focus to deliver scalable AI solutions.
Key Responsibilities:
  • Customer Success: Collaborate directly with the GTM team (Account Executives and Solutions Architects) to ensure smooth integration and successful deployment of ML solutions.
  • Demo / Proof of Concept (PoC): Build and present compelling PoCs that demonstrate the capabilities of our AI technology.
  • Application Build: Design, develop, and deploy end-to-end AI-powered applications tailored to customer needs.
  • Platform Features / Bug Fixes: Contribute to the internal ML platform, including adding features and resolving issues.
  • New Model Enablements: Integrate and enable new machine learning models into the existing platform or client environments.
  • Performance Optimizations: Improve system performance, efficiency, and scalability of deployed models and applications.
  • Partnership Enablement: Work closely with partners to enable joint AI solutions and ensure seamless collaboration.
Minimum Qualifications:
  • Bachelor's degree in Computer Science, Engineering, or a related technical field.
  • 5+ years of experience in a software engineering role, with a strong preference for customer-facing roles.
  • Robust coding skills required, preferably with proficiency in Python.
  • Demonstrated ability to lead and execute complex technical projects with a focus on customer success.
  • Strong interpersonal and communication skills; ability to thrive in dynamic, cross-functional teams.
Preferred Qualifications:
  • Master's degree in Computer Science, Engineering, or a related technical field.
  • Experience working in a startup or fast-paced environment.
  • Hands-on experience fine-tuning machine learning models, including supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF or RFT).
  • Solid understanding of generative AI, machine learning principles, and enterprise infrastructure.
Why Fireworks?
  • Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
  • Build What's Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
  • Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI-no bureaucracy, just results.
  • Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.

Fireworks AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

Apply