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Remote Prompt Engineering Jobs in Newark, NJ (NOW HIRING)

AI/ ML Engineer

New York, NY · Remote

$60 - $62/hr

US/ Canada- Remote Minimum exp. required: 8+ yrs. We are looking for a GenAI Engineer to design ... Implement prompt engineering, RAG (Retrieval-Augmented Generation), and fine-tuning techniques

Remote micro1 is engaging Business Document Experts (Excel, PowerPoint, Word) to participate in a ... Familiarity with conversational interactions or prompt engineering with language models is a plus ...

Software Engineer (Full-stack)

New York, NY · On-site +1

$110K - $135K/yr

Integrate and refine LLM workflows including prompt engineering, model orchestration, and backend/U ... If not, remote is always an option. 401(k) : Save for your future with tax advantages (and company ...

Remote OR Hybrid NYC- either OK (EST working hours) Start Date Is: ASAP Duration: (contract, perm ... Prompt Engineering as a Core Discipline: Write, rigorously test, and refine complex prompts and ...

Remote OR Hybrid NYC- either OK (EST working hours) Start Date Is: ASAP Duration: (contract, perm ... Prompt Engineering as a Core Discipline: Write, rigorously test, and refine complex prompts and ...

Remote OR Hybrid NYC- either OK (EST working hours) Start Date Is: Early May Duration: (contract ... Prompt Engineering as a Core Discipline: Write, rigorously test, and refine complex prompts and ...

Remote OR Hybrid NYC- either OK (EST working hours) Start Date Is: Early May Duration: (contract ... Prompt Engineering as a Core Discipline: Write, rigorously test, and refine complex prompts and ...

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Remote Prompt Engineering information

See Newark, NJ salary details

$18

$34

$50

How much do remote prompt engineering jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for remote prompt engineering in Newark, NJ is $34.57, according to ZipRecruiter salary data. Most workers in this role earn between $27.64 and $39.95 per hour, depending on experience, location, and employer.

How to make $1000 a week remotely?

Remote prompt engineering can generate $1000 or more weekly by freelancing on platforms like Upwork or Fiverr, building a strong portfolio, and offering specialized skills in AI and NLP. Consistent work, high-demand projects, and efficient time management are key to reaching this income level.

What engineer makes $500,000 a year?

Senior engineers in specialized fields such as software engineering, data engineering, or machine learning engineering can earn $500,000 or more annually, especially with extensive experience, advanced skills, and working in high-demand industries or companies. Compensation often includes base salary, bonuses, and stock options, particularly in tech giants or startups with significant growth potential.

What is the difference between Remote Prompt Engineering vs Remote Data Annotation Specialist?

AspectRemote Prompt EngineeringRemote Data Annotation Specialist
Required CredentialsBasic understanding of AI, NLP, and scripting skillsAttention to detail, familiarity with annotation tools, no formal certifications required
Work EnvironmentCollaborative with AI/ML teams, remote setupIndependent annotation tasks, remote or on-site
Industry UsageAI development, NLP projects, machine learningData labeling for AI training datasets
Search & Comparison IntentUnderstanding roles in AI development, job requirementsData labeling jobs, annotation tasks, related roles

Remote Prompt Engineering involves designing and refining prompts for AI models, requiring some technical skills and collaboration with AI teams. In contrast, Remote Data Annotation Specialists focus on labeling data to train AI systems, emphasizing attention to detail. Both roles are essential in AI development but differ in skills and daily tasks.

What are some common challenges faced by remote prompt engineers, and how can they be addressed?

Remote prompt engineers often face challenges related to communication and collaboration, especially when working across time zones and with interdisciplinary teams. Staying updated on rapidly evolving AI technologies and understanding nuanced user requirements can also be demanding. To address these, prompt engineers can leverage collaborative tools, maintain clear documentation, and participate in regular team syncs. Building a habit of continuous learning and engaging in knowledge-sharing sessions helps keep skills relevant and fosters a sense of connection despite remote work.

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

To thrive as a Remote Prompt Engineer, you need a strong background in natural language processing, programming (often Python), and an understanding of AI/ML concepts, typically supported by a relevant degree or industry experience. Familiarity with large language models (like OpenAI's GPT), prompt optimization tools, and version control systems such as Git is common. Creativity, problem-solving, and strong written communication are vital soft skills for designing effective prompts and collaborating remotely. These skills ensure the development of high-performing AI solutions and seamless teamwork in distributed environments.

Are prompt engineers still in demand?

Prompt engineering is a growing field as organizations seek professionals skilled in designing effective prompts for AI language models. Demand for prompt engineers is increasing across industries such as technology, healthcare, and finance, often requiring knowledge of AI tools and natural language processing. The role is expected to remain relevant as AI adoption expands.

What jobs make $3,000 a day?

High-paying jobs such as remote prompt engineering, specialized consulting, or executive roles can earn $3,000 or more per day, especially for professionals with advanced skills, experience, and in-demand expertise. These roles often require strong technical knowledge, certifications, and the ability to deliver high-value services on a freelance or contract basis.

What is remote prompt engineering?

Remote prompt engineering is the practice of designing and refining prompts for AI language models, such as ChatGPT, while working from a remote location. Prompt engineers craft instructions or questions to optimize the model’s responses for specific tasks or applications. This role typically involves understanding both the capabilities and limitations of AI systems, as well as the needs of end users or clients. Remote prompt engineers collaborate online with teams and may work for tech companies, research organizations, or as independent contractors.
What are the most commonly searched types of Prompt Engineering jobs in Newark, NJ? The most popular types of Prompt Engineering jobs in Newark, NJ are:
What are popular job titles related to Remote Prompt Engineering jobs in Newark, NJ? For Remote Prompt Engineering jobs in Newark, NJ, the most frequently searched job titles are:
What job categories do people searching Remote Prompt Engineering jobs in Newark, NJ look for? The top searched job categories for Remote Prompt Engineering jobs in Newark, NJ are:
What cities near Newark, NJ are hiring for Remote Prompt Engineering jobs? Cities near Newark, NJ with the most Remote Prompt Engineering job openings:
Infographic showing various Remote Prompt Engineering job openings in Newark, NJ as of July 2026, with employment types broken down into 88% Full Time, 8% Part Time, 3% Contract, and 1% Nights. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $71,904 per year, or $34.6 per hour.
Machine Learning Operations Engineer - Remote

Machine Learning Operations Engineer - Remote

NAVA Software Solutions

Jersey City, NJ • On-site, Remote

$76K - $102K/yr

Full-time

Re-posted 13 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

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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

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