ZipRecruiter

Log In

2

Remote Embedded Machine Learning Jobs in New Jersey

Gnostech

Software Engineer (US-Remote)

Marlton, NJ · On-site +1

Overview Location * US-Remote or Marlton, NJ area Job Title * Software Engineer Salary ... Build and integrate AI-enabled capabilities into applications, including machine learning models ...

Adidev Technologies

AI/ML

Hoboken, NJ · Remote

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... Support, even from afar, with our remote assistance. Regular salary reviews? You betcha! Ready to ...

Databricks

This role can be remote. The impact you will have: * Develop cutting-edge GenAI solutions ... Experience building production-grade machine learning deployments on AWS, Azure, or GCP * Graduate ...

Pepperidge Farm, Incorporated

Data Scientist

Camden, NJ · On-site +1

$109K - $150K/yr

You will leverage machine learning and advanced analytics to improve forecast accuracy, optimize ... Hybrid work model based in Camden, NJ (Monday & Friday remote; Tuesday-Thursday in-office) * 10-15 ...

Campbell's

Data Scientist

Camden, NJ · On-site +1

$109K - $150K/yr

You will leverage machine learning and advanced analytics to improve forecast accuracy, optimize ... Hybrid work model based in Camden, NJ (Monday & Friday remote; Tuesday-Thursday in-office) * 10-15 ...

Bank of America

Director; Senior Architect

Jersey City, NJ · On-site +1

$210K - $220K/yr

Remote work may be permitted within a commutable distance from the worksite. Required Skills ... Applying knowledge of Machine Learning, Natural Language Processing, advanced machine learning and ...

next page

Showing results 1-20

All JobsRemote Embedded Machine Learning JobsRemote Embedded Machine Learning Jobs in New Jersey

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 Jersey? The most popular types of Embedded Machine Learning jobs in New Jersey are:
What are popular job titles related to Remote Embedded Machine Learning jobs in New Jersey? For Remote Embedded Machine Learning jobs in New Jersey, the most frequently searched job titles are:
What job categories do people searching Remote Embedded Machine Learning jobs in New Jersey look for? The top searched job categories for Remote Embedded Machine Learning jobs in New Jersey are:
What cities in New Jersey are hiring for Remote Embedded Machine Learning jobs? Cities in New Jersey with the most Remote Embedded Machine Learning job openings:
Remote Embedded Machine Learning jobs near you
Machine Learning Operations Engineer - Remote

Machine Learning Operations Engineer - Remote

NAVA Software Solutions

Jersey City, NJ • On-site, Remote

$76K - $102K/yr

Full-time

Posted 26 days ago

Job description

NAVA Software solutions is looking for a Machine Learning Operations Engineer
Details:
Machine Learning Operations (MLOps) Engineer - AWS (with LLM Focus)
Location: Remote work
Duration: 12 months
Responsibilities:
  • LLM-Optimized MLOps Infrastructure: Design and implement MLOps infrastructure on AWS tailored for LLMs, leveraging services like SageMaker, EC2 (with GPU instances), S3, ECS/EKS, Lambda, and more.
  • LLM Deployment Pipelines: Build and manage CI/CD pipelines specifically for LLM deployment, addressing unique challenges like model size, inference optimization, and versioning.
  • LLMOps Practices: Implement LLMOps best practices for monitoring model performance, drift detection, prompt management, and feedback loops for continuous improvement.
  • RESTful API Development: Design and develop RESTful APIs to expose LLM capabilities to other applications and services, ensuring scalability, security, and optimal performance.
  • Model Optimization: Apply techniques like quantization, distillation, and pruning to optimize LLM models for efficient inference on AWS infrastructure.
  • Monitoring and Observability: Establish comprehensive monitoring and alerting mechanisms to track LLM performance, latency, resource utilization, and potential biases.
  • Prompt Engineering and Management: Develop strategies for prompt engineering and management to enhance LLM outputs and ensure consistency and safety.
  • Collaboration: Work closely with data scientists, researchers, and software engineers to integrate LLM models into production systems effectively.
  • Cost Optimization: Continuously optimize LLMOps processes and infrastructure for cost-efficiency while maintaining high performance and reliability.

Qualifications:
  • Experience: 3+ years of experience in MLOps or a related field, with hands-on experience in deploying and managing LLMs.
  • AWS Expertise: Strong proficiency in AWS services relevant to MLOps and LLMs, including SageMaker, EC2 (with GPU instances), S3, ECS/EKS, Lambda, and API Gateway.
  • LLM Knowledge: Deep understanding of LLM architectures (e.g., Transformers), training techniques, and inference optimization strategies.
  • Programming Skills: Proficiency in Python and experience with infrastructure-as-code tools (e.g., Terraform, CloudFormation), REST API frameworks (e.g., Flask, FastAPI), and LLM libraries (e.g., Hugging Face Transformers).
  • Monitoring: Familiarity with monitoring and logging tools for LLMs, such as Prometheus, Grafana, and CloudWatch.
  • Containerization: Experience with Docker and container orchestration (e.g., Kubernetes, ECS) for LLM deployment.
  • Problem Solving: Excellent problem-solving and troubleshooting skills in the context of LLMs and MLOps.
  • Communication: Strong communication and collaboration skills to effectively work with cross-functional teams
NAVA Software Solutions logo

About NAVA Software Solutions

Sourced by ZipRecruiter

NAVA is a strategic partner for companies seeking to develop or customize software and products. Our team of experts leverages cutting-edge technology and deep industry knowledge to provide customized solutions that drive business success. Whether you're looking to improve your operations, increase efficiency, or bring a new product to market, NAVA has the expertise and resources to help you achieve your goals. Trust us to be your partner in software and product development.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Rocky Hill, CT, US

Social media

Facebook

View All NAVA Software Solutions Jobs

Apply