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Remote Embedded Machine Learning Jobs in New York

Senior Machine Learning Engineer

New York, NY ยท Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ...

Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams to ... experience in Machine Learning , Data Science , Software Engineering , Computer Science ...

Senior Staff Machine Learning Engineer

Brooklyn, NY ยท On-site +1

$245K - $319K/yr

This position will be in Brooklyn, NY or for remote candidates based in the United States. Etsy is ... A foundational and practical understanding of machine learning principles and the critical steps ...

Senior Staff Machine Learning Engineer

New York, NY ยท On-site +1

$245K - $319K/yr

This position will be in Brooklyn, NY or for remote candidates based in the United States. Etsy is ... A foundational and practical understanding of machine learning principles and the critical steps ...

About Ramp Ramp is building the smart infrastructure for finance teams, embedded in the transaction ... You'll work at the intersection of machine learning, statistics, economics, and product strategy.

Sr. Data Analyst - Remote

Manhattan, NY ยท On-site +1

$94K - $119K/yr

Details: Sr. Data Analyst Duration: Full time / Direct Hire Location: 100% Remote but candidate ... SQL, Python, BigData, Data Analytics As a Data Analyst, you will leverage machine learning and ...

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Remote Embedded Machine Learning information

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

To thrive as a Remote Embedded Machine Learning Engineer, you need a solid background in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often supported by a degree in computer science, electrical engineering, or related fields. Familiarity with microcontrollers, edge AI frameworks (such as TensorFlow Lite or Edge Impulse), and version control systems is typically required. Strong problem-solving skills, effective communication, and self-motivation are essential soft skills for collaborating remotely and troubleshooting complex issues. These skills ensure successful deployment of intelligent solutions on resource-constrained devices and effective teamwork in distributed environments.

What is a Remote Embedded Machine Learning Engineer?

A Remote Embedded Machine Learning Engineer is a professional who develops and deploys machine learning models on embedded systems like microcontrollers, IoT devices, and edge hardware, all while working remotely. Their work involves optimizing algorithms to run efficiently on devices with limited computing power, memory, and battery life. These engineers typically use frameworks such as TensorFlow Lite or TinyML to design intelligent features that operate directly on hardware, enabling real-time decision-making without relying heavily on cloud connectivity. They collaborate with cross-functional teams and often troubleshoot both software and hardware issues from a remote location.

What is the difference between Remote Embedded Machine Learning vs Remote Data Scientist?

AspectRemote Embedded Machine LearningRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Electrical Engineering, or related fields; experience with embedded systems and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis and ML algorithms
Work EnvironmentEmbedded hardware devices, IoT systems, real-time processing environmentsCloud platforms, data analysis labs, remote offices
Employer & Industry UsageTech companies, IoT device manufacturers, automotive, roboticsFinance, healthcare, marketing, tech firms

Remote Embedded Machine Learning specialists focus on integrating ML models into embedded hardware for real-time applications, often working with IoT and robotics. In contrast, Remote Data Scientists analyze large datasets to extract insights, primarily working in cloud or office environments. Both roles require strong analytical skills but differ in technical focus and work settings.

What are some common challenges faced by Remote Embedded Machine Learning Engineers, and how can they be addressed?

Remote Embedded Machine Learning Engineers often encounter challenges related to hardware access, debugging embedded devices remotely, and collaborating with cross-functional teams across time zones. To address these, it's important to set up robust remote development environments, use simulation tools when physical hardware isn't available, and establish clear communication channels for effective teamwork. Regular virtual meetings and detailed documentation also help ensure alignment and smooth progress, despite the remote nature of the work.
What are the most commonly searched types of Embedded Machine Learning jobs in New York? The most popular types of Embedded Machine Learning jobs in New York are:
What cities in New York are hiring for Remote Embedded Machine Learning jobs? Cities in New York with the most Remote Embedded Machine Learning job openings:
Machine Learning Engineer - Search, Ranking & Personalization

Machine Learning Engineer - Search, Ranking & Personalization

Fuku

New York, NY โ€ข On-site, Remote

$190K - $260K/yr

Full-time

Re-posted yesterday


Job description

Machine Learning Engineer - Search, Ranking & Personalization
Stage: Seed
Founded: 2022
---
Key Job Information

  • <
  • i>Location: New York, NY / San Francisco, CA (Remote OK)
  • <
  • i>Employment Type: Full-Time
  • <
  • i>Experience Level: 3+ years
  • <
  • i>Salary Range: $190,000 - $260,000 per year
  • <
  • i>Equity: Competitive equity package
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  • i>Visa Sponsorship: H-1B, O-1, OPT
    ---
    About the Company
    Client is a fast-growing shopping platform with over 350,000 active users and a 90% retention rate. The company is focused on building intelligent, personalized search and ranking systems to help users discover and trust products at scale. The team is composed of experienced engineers from leading consumer tech companies such as Pinterest and Amazon.
    ---
    Role Summary
    As a Machine Learning Engineer at Client's company, you will join the ML team to design, build, and scale machine learning systems that drive search, ranking, and personalization across a platform serving hundreds of millions of items daily. This is a highly impactful role where your work directly influences user retention and trust. You will collaborate with a world-class team of engineers and play a key part in defining the ML search and personalization strategy from the ground up. The position is open to fully remote candidates.
    ---
    Key Responsibilities
  • D
  • esign, train, and deploy large-scale search, ranking, and personalization models.
  • H
  • andle hundreds of millions of items daily with high performance and reliability.
  • C
  • ollaborate closely with backend and infrastructure teams to integrate ML models into production (GraphQL, Prisma, Node.js, Python, gRPC/Protobuf).
  • C
  • ontinuously improve model accuracy and system scalability.
  • C
  • ontribute to product direction and technical roadmap for Client's ML systems.
    ---
    Requirements
    Must-Have Qualifications:
  • M
  • inimum of 3+ years professional experience building and deploying ML models in production.
  • P
  • roven experience with ranking, recommendation, or personalization systems.
  • P
  • roficiency in PyTorch and large-scale data processing for real-time inference.
  • S
  • trong backend integration experience (GraphQL, Prisma, Node.js, Python, gRPC/Protobuf).
  • W
  • illingness to work in a high-intensity, fast-paced startup environment.
  • B
  • ased in New York or remote in San Francisco.
    Preferred Background:
  • C
  • urrent or prior experience at companies like DoorDash, Etsy, Pinterest, Amazon, or eBay.
  • P
  • revious work on consumer-facing search or recommendation products.
    ---
    Benefits & Perks
  • $
  • 190K-$260K base salary plus competitive equity.
  • D
  • irect impact on a core product with a massive, high-retention user base.
  • W
  • ork alongside top-tier engineers from leading consumer tech companies.
  • F
  • ast-paced startup culture with rapid iteration and experimentation.
  • O
  • pportunity to build the ML search and personalization strategy from scratch.
    ---
    Interview Process
    1. Intro call with Head of Recruiting
    2. Technical Interview
    3. Coding Interview
    4. CTO Interview
    5. Onsite Interview
    6. Offer Extended
    7. Hire
    ---
    Candidate Guidelines
    Green Flags:
  • E
  • xperience solving large-scale consumer search/ranking challenges (e.g., Pinterest, Meta, TikTok, Amazon Ads).
  • S
  • trong track record shipping high-impact ML features in consumer products.
  • E
  • arly-stage or startup experience with end-to-end ownership of ML pipelines.
  • D
  • emonstrated "builder" mindset - side projects, prototypes, hackathon wins.
  • H
  • igh intrinsic motivation and interest in future entrepreneurship.
    Red Flags:
  • P
  • rimarily B2B search experience with limited data complexity.
  • R
  • esearch-only background without production deployment.
  • P
  • refers management over hands-on technical work.
  • S
  • truggles with ambiguity or high-intensity work environments.
  • U
  • nwilling to relocate or adapt to NYC-based team culture.
    ---
    Ideal Companies
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  • mazon
  • e
  • Bay
  • P
  • interest
  • D
  • oorDash
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  • tsy


    Fuku logo

    About Fuku

    Sourced by ZipRecruiter

    Industry

    Food services and drinking places

    Company size

    51 - 200 Employees

    Headquarters location

    New York, NY, US

    Year founded

    2015