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Senior Embedded Machine Learning Jobs in Mount Laurel, NJ

Senior Data Scientist AI for Science, Research Intelligence & Knowledge Discovery Build AI That ... Design, develop, and deploy advanced machine learning, NLP, retrieval, and generative AI solutions ...

Senior Data Scientist AI for Science, Research Intelligence & Knowledge Discovery Build AI That ... Design, develop, and deploy advanced machine learning, NLP, retrieval, and generative AI solutions ...

Senior ML Ops Engineer

Philadelphia, PA · On-site

$99K - $137K/yr

As a Senior Machine Learning Ops Engineer, you will bridge Data Science and Engineering to develop AI-based features and ensure the reliability and scalability of machine learning models and services.

Senior Data Scientist

Camden, NJ · On-site

$109 - $150/hr

Lead the end‑to‑end development of advanced analytics solutions, including Machine Learning ... Senior leadership teams responsible for strategic business initiatives * External retail partners ...

Lead the end-to-end development of advanced analytics solutions, including Machine Learning, Deep ... Senior leadership teams responsible for strategic business initiatives * External retail partners ...

Lead the end-to-end development of advanced analytics solutions, including Machine Learning, Deep ... Senior leadership teams responsible for strategic business initiatives * External retail partners ...

Senior ML Ops Engineer

Philadelphia, PA · On-site

$99K - $137K/yr

In this role, the Senior Machine Learning Engineer will bridge Data Science and Engineering to develop AI-based features and ensure the deployment of secure, reliable, and scalable machine learning ...

We are seeking a creative, and curious Senior Data Science Software Engineer to join our team. In ... Lead the end-to-end development of machine learning and data products aligned to business ...

Partners with senior leadership to understand and probe business processes in order to develop ... Strong experience utilizing statistical and machine learning methods required. Experience with ...

HOW YOU WILL MAKE HISTORY HERE As a Senior Data Scientist, you will serve as a hands-on technical ... Collaborate with data engineering teams to enhance data and machine learning platforms, evaluate ...

Showing results 21-40

Senior Embedded Machine Learning information

See Mount Laurel, NJ salary details

$74.8K

$143.4K

$191.6K

How much do senior embedded machine learning jobs pay per year?

As of Aug 21, 2026, the average yearly pay for senior embedded machine learning in Mount Laurel, NJ is $143,372.00, according to ZipRecruiter salary data. Most workers in this role earn between $122,800.00 and $160,900.00 per year, depending on experience, location, and employer.

What does a senior embedded machine learning engineer do?

A Senior Embedded Machine Learning engineer designs, develops, and optimizes machine learning models to run efficiently on resource-constrained embedded devices such as microcontrollers, IoT devices, and edge hardware. They are responsible for integrating ML algorithms with embedded systems, ensuring low latency and minimal power consumption. Their work often involves collaborating with hardware engineers and software developers to deploy intelligent features in products like smart sensors, wearables, and autonomous systems.

What are the key skills and qualifications needed to thrive as a senior embedded machine learning engineer?

To thrive as a Senior Embedded Machine Learning Engineer, you need expertise in embedded systems, machine learning algorithms, and programming languages like C/C++ and Python, often backed by an advanced degree in computer science or electrical engineering. Familiarity with tools such as TensorFlow Lite, ONNX, and embedded hardware platforms (e.g., ARM Cortex-M, NVIDIA Jetson) is typically required. Strong problem-solving, project management, and communication skills distinguish top performers in this role. These capabilities are crucial for efficiently deploying optimized machine learning models on resource-constrained devices and effectively collaborating across multidisciplinary teams.

What are some common challenges faced by senior embedded machine learning engineers when deploying models on edge devices?

Senior Embedded Machine Learning Engineers often encounter challenges such as optimizing model size and inference speed to fit within the limited computational resources and memory of edge devices. Balancing accuracy and performance while minimizing power consumption is critical, especially for battery-operated products. Additionally, integrating models with existing embedded software and ensuring reliable, real-time operation can require close collaboration with hardware and firmware teams. Staying current with advancements in model compression and hardware acceleration is also essential for success in this role.

What is the difference between Senior Embedded Machine Learning vs Embedded Software Engineer?

AspectSenior Embedded Machine LearningEmbedded Software Engineer
Required CredentialsBachelor's/Master's in CS, EE, or related; experience in ML and embedded systemsBachelor's in CS, EE, or related; strong programming skills in C/C++
Work EnvironmentDeveloping ML models for embedded devices, hardware integrationDesigning and implementing embedded software for devices
Industry UsageAI/ML-focused companies, IoT, consumer electronicsAutomotive, industrial, consumer electronics

While both roles involve embedded systems, Senior Embedded Machine Learning focuses on integrating ML models into hardware, requiring knowledge of AI and data science. Embedded Software Engineers primarily develop software for embedded devices, emphasizing firmware and system-level programming. The roles overlap in embedded environment skills but differ in their core focus on AI versus traditional software development.

Senior Data Scientist

Elsevier

Philadelphia, PA • On-site

Full-time

Re-posted 10 days ago


Elsevier rating

8.9

Company rating: 8.9 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

32nd of 495 rated business services


Job description

Senior Data Scientist
AI for Science, Research Intelligence & Knowledge Discovery
Build AI That Helps Advance Human Knowledge
What if your next AI model could help accelerate a medical breakthrough, uncover a critical scientific insight, or help researchers solve some of humanity's greatest challenges?
At Elsevier, data science is about far more than algorithms and model performance. It is about applying advanced AI to help researchers, clinicians, educators, and institutions discover knowledge, assess evidence, generate insights, and advance science for the benefit of society.
Every day, millions of researchers rely on our products to navigate an ever-growing universe of scientific information. As a Senior Data Scientist, you will help build the intelligent systems that make scientific knowledge more discoverable, trustworthy, connected, and actionable.
This is AI with purpose. This is technology in service of scientific progress.
About the Role
As a Senior Data Scientist, you will design, build, evaluate, and scale advanced AI solutions that power scientific discovery, research intelligence, knowledge enrichment, and decision support across the global research ecosystem.
You will work on some of the most challenging problems in applied AI, combining machine learning, natural language processing, large language models, retrieval systems, knowledge graphs, and generative AI to help researchers uncover insights faster and make better decisions.
Success in this role requires deep technical expertise, sound judgment, scientific rigor, and the ability to transform complex problems into trusted, production-ready AI solutions that create measurable impact.
About the team
As part of a growing team of Data Scientists, you will take on some of the hardest problems in science. This team is building intelligent systems that can reason across scientific publications, research data, knowledge graphs, ontologies, metadata, taxonomies, citations, and content spanning every scientific discipline
What You'll Do
  • Design, develop, and deploy advanced machine learning, NLP, retrieval, and generative AI solutions that support scientific discovery and knowledge exploration.
  • Build and optimize LLM-powered applications, including question answering, literature summarization, semantic search, research insight generation, and evidence-grounded AI experiences.
  • Develop retrieval-augmented generation (RAG) systems that connect AI models with trusted scientific and scholarly content.
  • Create intelligent capabilities for search, ranking, recommendation, entity extraction, classification, enrichment, and decision support.
  • Design evaluation frameworks that measure quality, relevance, reliability, grounding, trustworthiness, and user impact.
  • Integrate knowledge graphs, ontologies, taxonomies, citations, metadata, and scientific domain knowledge into AI workflows.
  • Partner with engineering teams to produce, monitor, optimize, and continuously improve AI systems at scale.
  • Lead technical discovery, influence solution architecture, and guide methodological decisions across initiatives.
  • Mentor fellow data scientists and contribute to a culture of technical excellence, experimentation, and responsible AI.
  • Collaborate closely with Product, Engineering, Research, Editorial, UX, and domain experts to solve complex scientific and business challenges.

What We're Looking For
  • Significant hands-on experience in Data Science, Machine Learning, Artificial Intelligence, NLP, Information Retrieval, Statistics, Computer Science, or a related quantitative discipline.
  • Advanced expertise in developing and deploying machine learning, NLP, retrieval, and generative AI solutions in production environments.
  • Experience working with modern LLMs, prompt engineering, model evaluation, retrieval systems, and AI-powered workflows.
  • Extensive Python programming skills and a track record of building maintainable, production-quality software.
  • Experience designing and implementing RAG systems, semantic search, vector retrieval, embeddings, ranking, or recommendation solutions.
  • Deep understanding of machine learning fundamentals, experimentation, model evaluation, statistical analysis, and performance measurement.
  • Experience with modern AI and ML frameworks such as PyTorch, TensorFlow, Hugging Face, LangChain, LangGraph, or equivalent technologies.
  • Experience working with large-scale structured, semi-structured, and unstructured datasets, particularly text-rich or content-heavy data.
  • A passion for advancing science, expanding access to knowledge, and building AI systems that create meaningful real-world impact.

Why Join Elsevier
Because your work will matter.
You will help build AI systems that enable researchers to discover knowledge faster, uncover hidden connections, assess evidence more effectively, and accelerate scientific progress around the world.
You will have the opportunity to:
  • Solve some of the most challenging AI problems in science and knowledge discovery.
  • Work with one of the world's richest collections of scientific, biomedical, and scholarly data.
  • Build next-generation AI systems using LLMs, retrieval, knowledge graphs, semantic search, and generative AI.
  • Create trusted technologies that support researchers, clinicians, educators, institutions, and innovators worldwide.
  • Influence how AI is designed, evaluated, governed, and trusted in high-impact scientific environments.
  • Collaborate with exceptional colleagues across data science, engineering, product, research, editorial, and domain expertise.
  • Mentor others while helping shape the future of AI-powered scientific discovery.
  • Contribute directly to a mission dedicated to advancing science, improving health outcomes, and expanding human knowledge.

At Elsevier, AI is not just about what technology can do. It is about what humanity can achieve when knowledge becomes more accessible, discoverable, and actionable.
That is the impact of your work.
U.S. National Base Pay Range: $95,300 - $158,800. Geographic differentials may apply in some locations to better reflect local market rates.If performed in Maryland, the base pay range is $100,100 - $166,800.If performed in New York, the base pay range is $104,800 - $174,700.If performed in New York City, the base pay range is $114,300 - $190,500.If performed in Rochester, NY, the base pay range is $95,300 - $158,800.If performed in New Jersey, the base pay range is $112,574 - $179,826.This job is eligible for an annual incentive bonus.
We know your well-being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location.
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