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Helix AI Engineer, Generative AI

San Jose, CA · On-site

We are looking for a Helix AI Engineer, Generative AI to build and scale generative models that enable robots to understand, simulate, and interact with the physical world. This role focuses on ...

Johnson & Johnson

Data and Generative AI Engineer

Raritan, NJ · On-site

$117K - $140K/yr

We are seeking a skilled and motivated Data and Generative AI Engineer to join our dynamic team. The candidate will have a strong background in software development, data engineering, Generative AI ...

Jj

Data and Generative AI Engineer

New Brunswick, NJ

$118K - $141K/yr

We are seeking a skilled and motivated Data and Generative AI Engineer to join our dynamic team. The candidate will have a strong background in software development, data engineering, Generative AI ...

Elliot Partnership

Generative AI Developer

New York, NY · On-site

* Generative AI Developer for a leading Quant Firm * Hybrid working in New York * Highly competitive ... engineer, if you're passionate about GAI, we want to hear from you! Why Join Us? * Work on cutting ...

Jj

Data and Generative AI Engineer

Raritan, NJ

$117K - $140K/yr

We are seeking a skilled and motivated Data and Generative AI Engineer to join our dynamic team. The candidate will have a strong background in software development, data engineering, Generative AI ...

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How much do freelance generative ai engineer jobs pay per hour?

As of Jul 5, 2026, the average hourly pay for freelance generative ai engineer in the United States is $47.71, according to ZipRecruiter salary data. Most workers in this role earn between $24.28 and $61.78 per hour, depending on experience, location, and employer.

What are the most common challenges faced by freelance Generative AI Engineers when working with clients on custom AI solutions?

Freelance Generative AI Engineers often encounter challenges such as managing client expectations regarding project timelines and the complexity of AI models, especially when clients have limited technical knowledge. Ensuring clear communication about data requirements, model capabilities, and ethical considerations is crucial for successful project delivery. Additionally, freelancers must stay up to date with rapidly evolving AI frameworks and tools while balancing multiple projects and deadlines. Building robust documentation and maintaining transparency throughout the development process can help mitigate misunderstandings and foster long-term client relationships.

What is a Freelance Generative AI Engineer?

A Freelance Generative AI Engineer is a professional who works independently to design, build, and deploy artificial intelligence models that can generate new data, such as text, images, or music. These engineers typically specialize in technologies like generative adversarial networks (GANs), large language models (LLMs), and other machine learning frameworks. They collaborate with clients or companies on a project-by-project basis, offering expertise in AI model development, fine-tuning, and integration. Being freelance, they have the flexibility to work with multiple clients across various industries, including tech, media, and entertainment.

What are the key skills and qualifications needed to thrive as a Freelance Generative AI Engineer, and why are they important?

To thrive as a Freelance Generative AI Engineer, you need a deep understanding of machine learning, neural networks, and programming languages such as Python, often supported by a degree in computer science or related field. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms, and experience with AI model deployment are typically required. Strong problem-solving abilities, adaptability, and effective communication help you collaborate with clients and address evolving project needs. These skills are crucial for developing innovative AI solutions, meeting client expectations, and staying competitive in a rapidly changing field.
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Freelance Generative Ai Engineer jobs near you
Infographic showing various Freelance Generative Ai Engineer job openings in the United States as of June 2026, with employment types broken down into 96% Full Time, 1% Part Time, and 3% Contract. Highlights an 66% Physical, 3% Hybrid, and 31% Remote job distribution, with an average salary of $99,230 per year, or $47.7 per hour.
Senior MLOps & Generative AI Engineer - Remote

Senior MLOps & Generative AI Engineer - Remote

Sentara Healthcare

Centre, AL • On-site, Remote

$98K - $135K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago

Sentara Health rating

6.9

Company rating: 6.9 out of 10

Based on 390 frontline employees who took The Breakroom Quiz

483rd of 877 rated healthcare providers

Job description

City/State
Virginia Beach, VA
Work Shift
First (Days)
Overview:
Sentara is hiring a Senior MLOps & Generative AI Engineer!
This position is fully remote!
Candidates must reside in one of the following states:
Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Washington, West Virginia, Wisconsin, or Wyoming.
Overview
We are seeking a highly skilled and experienced Senior MLOps & Generative AI Engineer to join our growing AI organization and help advance current and future initiatives applying machine learning, deep learning, NLP, and Generative AI technologies to improve healthcare outcomes and operational excellence.
This role combines two critical focus areas:
  • MLOps Engineering - building and scaling enterprise-grade ML infrastructure, deployment pipelines, observability, governance, and automation capabilities.
  • Generative AI Engineering - designing, architecting, deploying, and optimizing secure, production-ready GenAI applications and platforms leveraging LLMs, RAG architectures, vector databases, prompt orchestration, and AI evaluation frameworks.

As a Senior Engineer, you will partner closely with AI Scientists, Data Engineers, Software Engineers, Architects, and Product teams to operationalize AI/ML and Generative AI solutions at enterprise scale. You will play a key role in shaping the organization's AI platform strategy, driving best practices, and delivering scalable, secure, and reliable AI systems in production healthcare environments.
Key Responsibilities
MLOps Engineering Responsibilities
  • Design, build, and maintain scalable ML infrastructure and pipelines supporting model training, deployment, monitoring, governance, and lifecycle management.
  • Develop and optimize CI/CD pipelines for machine learning and AI workloads across development, staging, and production environments.
  • Build reusable ML platform capabilities including feature stores, model registries, experimentation frameworks, artifact management, and deployment automation.
  • Implement scalable orchestration and workflow solutions for batch and real-time ML inference workloads.
  • Create robust monitoring systems to measure model performance, detect model drift, monitor data quality, and ensure production reliability.
  • Develop automation tools and self-service capabilities to improve the efficiency, scalability, and reliability of MLOps processes.
  • Collaborate with Data Scientists and Software Engineers to streamline the ML lifecycle from experimentation through enterprise production deployment.
  • Apply software engineering best practices to AI/ML systems including testing, observability, resiliency, security, versioning, and infrastructure-as-code.
  • Identify gaps and improvement opportunities within the organization's ML platform ecosystem and architect scalable solutions to address them.
  • Support enterprise AI governance, compliance, auditability, and model risk management requirements.
  • Ensure platform scalability, reliability, security, and operational excellence across AI/ML systems.

Generative AI Engineering Responsibilities
  • Lead the architecture, design, and deployment of enterprise Generative AI solutions leveraging LLMs, foundation models, and agentic AI systems.
  • Design and implement Retrieval-Augmented Generation (RAG) pipelines using vector databases, embeddings, semantic search, reranking, and retrieval optimization strategies.
  • Build scalable LLM orchestration frameworks using technologies such as LangChain, LlamaIndex, Semantic Kernel, or equivalent frameworks.
  • Develop advanced prompt engineering strategies, prompt chaining, context management, and agent workflows to improve LLM accuracy and reliability.
  • Evaluate and implement fine-tuning, parameter-efficient tuning, and prompt-based optimization approaches for domain-specific use cases.
  • Build AI evaluation and benchmarking frameworks to measure hallucination rates, response quality, grounding accuracy, toxicity, bias, latency, and business performance metrics.
  • Implement AI safety guardrails, governance controls, content filtering, and responsible AI practices for enterprise healthcare environments.
  • Design scalable GenAI APIs and microservices supporting high-throughput enterprise AI applications.
  • Optimize GenAI systems for cost, latency, throughput, and inference performance across cloud and hybrid environments.
  • Integrate enterprise data sources, healthcare systems, and knowledge repositories into secure GenAI workflows.
  • Research and evaluate emerging GenAI technologies, open-source frameworks, and foundation models to drive innovation and continuous improvement.
  • Develop architecture diagrams, technical roadmaps, implementation strategies, and executive-level documentation for enterprise AI initiatives.
  • Collaborate with cybersecurity, compliance, and infrastructure teams to ensure secure and compliant deployment of GenAI solutions involving PHI and sensitive healthcare data.
  • Contribute to the development of AI platform standards, reusable GenAI accelerators, templates, and engineering best practices.

Required Qualifications
  • 5+ years of experience building and deploying production software, ML systems, or AI platforms.
  • 1+ years of hands-on experience building production Generative AI or LLM-based applications.
  • Strong programming skills in Python and experience with software engineering best practices.
  • Experience with major deep learning and LLM frameworks such as PyTorch, Hugging Face Transformers, TensorFlow, or equivalent.
  • Hands-on experience implementing RAG architectures, vector search, embeddings, prompt engineering, and LLM orchestration frameworks.
  • Experience with vector databases such as Pinecone, Weaviate, Chroma, FAISS, Milvus, or equivalent technologies.
  • Experience deploying AI/ML systems in cloud environments including AWS, Azure, or GCP.
  • Strong understanding of APIs, distributed systems, microservices, and scalable backend architectures.
  • Experience with Kubernetes, containerization, orchestration, and cloud-native infrastructure.
  • Experience implementing CI/CD pipelines, infrastructure automation, and MLOps best practices.
  • Experience building monitoring, observability, and alerting solutions for ML and AI systems.
  • Strong understanding of AI/ML lifecycle management, governance, model versioning, and production operations.
  • Experience designing secure, scalable, production-ready AI platforms and services.
  • Strong communication and collaboration skills with the ability to work across technical and business teams.

Preferred Qualifications
  • Previous experience implementing Generative AI and MLOps solutions within healthcare environments.
  • Experience working with EPIC or healthcare interoperability platforms.
  • Understanding of HIPAA, PHI handling, healthcare compliance, and responsible AI practices.
  • Experience with AI governance frameworks, LLM evaluation methodologies, and AI safety tooling.
  • Experience with GPU infrastructure optimization and scalable inference architectures.
  • Familiarity with multi-agent AI systems and autonomous workflows.
  • Experience with event-driven architectures, streaming pipelines, and real-time inference systems.
  • Exposure to model fine-tuning techniques including LoRA, PEFT, RLHF, or domain adaptation strategies.
  • Experience with enterprise AI platform architecture and internal developer platforms.
  • Prior experience mentoring engineers and leading technical initiatives.

Education
  • 5+ years of relevant experience with a degree (Required)

or
  • 7+ years of relevant experience without a degree (Required)
  • Experience in lieu of Bachelor's Degree.

Certification/Licensure
  • No specific certification or licensure requirements

Experience
  • 5 to 7 years of relevant experience

We provide market-competitive compensation packages, inclusive of base pay, incentives, and benefits. The base pay rate for Full Time employment is: 91,416.00 - 152,380.80. Additional compensation may be available for this role such as shift differentials, standby/on-call, overtime, premiums, extra shift incentives, or bonus opportunities.
Keywords: Talroo-IT, MLOps, Gen AI, LLM, AWS, Azure, GCP, AI/ML, Python, PyTorch, Hugging Face Transformers, TensorFlow, RAG, EPIC, HIPAA, AI Governance
Benefits: Caring For Your Family and Your Career
• Medical, Dental, Vision plans
• Adoption, Fertility and Surrogacy Reimbursement up to 10,000
• Paid Time Off and Sick Leave
• Paid Parental & Family Caregiver Leave
• Emergency Backup Care
• Long-Term, Short-Term Disability, and Critical Illness plans
• Life Insurance
• 401k/403B with Employer Match
• Tuition Assistance - 5,250/year and discounted educational opportunities through Guild Education
• Student Debt Pay Down - 10,000
• Reimbursement for certifications and free access to complete CEUs and professional development
• Pet Insurance
• Legal Resources Plan
• Colleagues have the opportunity to earn an annual discretionary bonus if established system and employee eligibility criteria is met.
Sentara Health is an equal opportunity employer and prides itself on the diversity and inclusiveness of its close to an almost 30,000-member workforce. Diversity, inclusion, and belonging is a guiding principle of the organization to ensure its workforce reflects the communities it serves.
In support of our mission "to improve health every day," this is a tobacco-free environment.
For positions that are available as remote work, Sentara Health employs associates in the following states:
Alabama, Delaware, Florida, Georgia, Idaho, Indiana, Kansas, Louisiana, Maine, Maryland, Minnesota, Nebraska, Nevada, New Hampshire, North Carolina, North Dakota, Ohio, Oklahoma, Pennsylvania, South Carolina, South Dakota, Tennessee, Texas, Utah, Virginia, Washington, West Virginia, Wisconsin, and Wyoming.

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