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Senior Embedded Machine Learning Jobs in New Jersey

SonSoft Inc.

Sr. Data Scientist

Newark, NJ · On-site

They are seeking a Senior Data Scientist with extensive experience in machine learning algorithms and strong skills in Text Mining and Natural Language Processing. Responsibilities : • 10 to 15 ...

Citigroup Inc.

Sr. Data Scientist - Vice President

Jersey City, NJ · On-site

$142.32 - $213.48/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Job Summary The Sr. Data Scientist is responsible for establishing and implementing new or revised ... Developing complex machine learning models using the Python AI/ML stack. * Designing and ...

Socket.dev

Senior Data Scientist

Newark, NJ · On-site

$97.30 - $178.80/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

As a Senior Data Scientist on Individual Life Insurance (ILI) Data Science team, you will partner ... Partner with machine learning engineers to productionized machine learning models. Partner with ...

Tiger Analytics Inc.

Senior AI Engineer

Jersey City, NJ · Remote

$109K - $149K/yr

You will leverage advanced machine learning techniques, frameworks, and large datasets to create innovative products and solutions. As a Senior AI Engineer, you will work closely with cross ...

Tiger Analytics Inc.

Senior AI Engineer

Jersey City, NJ · On-site

$109K - $149K/yr

You will leverage advanced machine learning techniques, frameworks, and large datasets to create innovative products and solutions. As a Senior AI Engineer, you will work closely with cross ...

Novo Nordisk A/S

Senior Data Scientist

Plainsboro, NJ · On-site

$120.30 - $222.60/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Senior Data Scientist will build machine learning-based tools and processes within the company's current big data infrastructure such as recommendation engines, automated propensity scoring ...

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All JobsEmbedded Machine Learning JobsSenior Embedded Machine Learning JobsSenior Embedded Machine Learning Jobs in New Jersey

Senior Embedded Machine Learning information

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.

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 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 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 most commonly searched types of Embedded Machine Learning jobs in New Jersey?

The most popular types of Embedded Machine Learning jobs in New Jersey are:

What cities in New Jersey are hiring for Senior Embedded Machine Learning jobs?

Cities in New Jersey with the most Senior Embedded Machine Learning job openings:

Senior Embedded Machine Learning jobs near you

Lead Machine Learning Engineer (Locals to NJ preferred) - W2 Role

Saransh Inc

Weehawken, NJ • On-site

$111K - $146K/yr

Contractor

Re-posted just now

Job description

Role: Lead / Senior Machine Learning Enginee
Location: Weehawken, NJ (Day 1 Onsite) - Locals preferred
Job Type: W2 Contract
 
Position Overview:
  • We are seeking a highly skilled and experienced Lead/ Senior Machine Learning Engineer with expertise in Python and hands-on experience designing innovative solutions using Agentic systems and modeling large language models (LLMs).
  • The ideal candidate will hold an Azure Certified AI Practitioner certification and demonstrate deep knowledge of Azure’s AI services and data engineering tools.
 
Key Responsibilities:
AI and Agentic Solutions Development:
  • Design, develop, and implement agentic systems for real-time decision-making processes.
  • Integrate multimodal AI agents capable of proactive problem-solving using machine learning and automation.
  • Collaborate with stakeholders to architect solutions that align with organizational goals.
LLM Development and Optimization:
  • Build, customize, and fine-tune large language models (LLMs) for diverse business applications.
  • Research and experiment with LLM architectures to optimize performance for specific use cases like NLP, conversational AI, and summarization.
  • Deploy LLMs efficiently on Azure services such as Azure Machine Learning, OpenAI Service, and Cognitive Services.
Data Engineering Expertise:
  • Architect and maintain complex data pipelines and frameworks on Azure.
  • Work with relational and non-relational databases to preprocess and manage datasets for AI models.
  • Leverage Azure tools like Data Factory, Synapse Analytics, and Databricks for ETL processes and advanced analytics workflows.
Python Development and Software Engineering:
  • Write high-quality, scalable Python code for machine learning and data engineering applications.
  • Develop reusable libraries for AI models and data processing workflows.
  • Collaborate with DevOps teams to ensure robust CI/CD pipelines and deploy production-ready solutions in cloud environments.
Collaboration and Leadership:
  • Mentor and guide junior engineers on best practices in data engineering and machine learning.
  • Collaborate with cross-functional teams, including data scientists, product managers, and business analysts.
  • Proactively contribute to strategic roadmaps for AI-powered business solutions.
Required Qualifications:
  • Azure Certified AI Practitioner (or equivalent Azure certification in AI and data engineering).
  • Demonstrable expertise in Python, with advanced knowledge of libraries such as Pandas, NumPy, PyTorch, TensorFlow, and LangChain.
  • Extensive experience designing and building Agentic solutions (e.g., autonomous agents capable of advanced decision-making and orchestration).
  • Hands-on experience with modeling and deploying LLMs (fine-tuning, prompt engineering, optimization).
  • Proficiency with Microsoft Azure ecosystem, including services like Azure Machine Learning, OpenAI Service, Cognitive Services, and Databricks.
  • Strong understanding of machine learning, natural language processing (NLP), and generative AI concepts.
  • Familiarity with best practices in data engineering, such as data modeling, schema design, ETL processes, and pipeline optimization.
Preferred Qualifications:
  • Advanced degree (Master’s or PhD) in Computer Science, Data Engineering, AI/ML, or a related field.
  • Experience with integrating LLMs into production environments for real-world applications (e.g., chatbots, document summarization, generative design).
  • Knowledge of distributed computing frameworks (e.g., Spark, Hadoop).
  • Familiarity with versioning tools (e.g., Git), containerization (e.g., Docker), and orchestration (e.g., Kubernetes).