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Remote Generative Ai Engineer Jobs in Silver Spring, MD

PhoenixTeam

GenAI Engineer

Arlington, VA · Remote

Applied AI Engineering & Delivery * Design, implement, fine-tune, and deploy generative AI and ML solutions aligned to real business use cases. * Translate technical and business requirements into ...

B&A

AI-ML Developer

Ashburn, VA · On-site +1

Description AI-ML Developer: At B&A, we foster and embrace a distinct set of values that we live by ... Develop, train, and deploy advanced AI/ML models, including generative AI techniques like large ...

Booz Allen Hamilton, Inc.

AI/ML Engineer, Mid

Chantilly, VA · On-site +1

$77K - $176K/yr

Remote Work: No Job Number: R0245169 Location: Chantilly,VA,US Share job via: Share AI/ML Engineer ... Experience working with LLMs, generative AI systems, or agentic frameworks * Experience with Python ...

Global Alliant Inc

AI Engineer

Baltimore, MD · Remote

Remote Job Duration: Fulltime Client: Federal Criteria- Need ship because of federal regulations ... experience in AI/ML, Data Science, Data Engineering, or Analytics. * 3+ years of hands-on ...

Global Alliant Inc

AI Engineer

Baltimore, MD · Remote

Remote Job Duration: Fulltime Client: Federal Criteria- Need ship because of federal regulations ... experience in AI/ML, Data Science, Data Engineering, or Analytics. * 3+ years of hands-on ...

ManTech

AI Engineer

Washington, DC · On-site +1

$141K - $236K/yr

The AI Engineer supports the development and operationalization of advanced AI and agentic AI ... For Remote Opportunities), education and certifications as well as Federal Government Contract ...

Interon IT Solutions

ServiceNow AI Developer

Chantilly, VA · Remote

$55.25 - $76/hr

The role will focus on developing intelligent workflows, implementing generative AI capabilities ... Implement prompt engineering strategies and retrieval-augmented generation (RAG) patterns. * Train ...

SAIC

AI Engineer - SETA

Columbia, MD · On-site +1

$240K - $280K/yr

None Potential for Remote Work: ORA_ON_SITE Description Varen, an SAIC Company is seeking an AI Engineer - SETA to join our team. This position is located in Columbia, MD and requires a TS/SCI with ...

InterImage

Software Engineer

Arlington, VA · Remote

This role is ideal for candidates who are passionate about software engineering, curious about Generative AI, and eager to help modernize how technology supports national security and operational ...

Blend360

AI Engineering Sr Director

Columbia, MD · On-site +1

$251K/yr

We are seeking a highly accomplished and dynamic Director, AI & Generative Solutions to join our ... Programming experience in Python, with experience in developing and deploying production-grade AI ...

InterImage

Software Engineer

Arlington, VA · On-site +1

This role is ideal for candidates who are passionate about software engineering, curious about Generative AI, and eager to help modernize how technology supports national security and operational ...

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Showing results 41-60

All JobsGenerative Ai Engineer JobsRemote Generative Ai Engineer JobsRemote Generative Ai Engineer Jobs in Silver Spring, MD

Remote Generative Ai Engineer information

See Silver Spring, MD salary details

$39.3K

$119.8K

$198K

How much do remote generative ai engineer jobs pay per year?

As of Aug 6, 2026, the average yearly pay for remote generative ai engineer in Silver Spring, MD is $119,778.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,800.00 and $156,600.00 per year, depending on experience, location, and employer.

What is the difference between Remote Generative Ai Engineer vs Remote Machine Learning Engineer?

AspectRemote Generative Ai EngineerRemote Machine Learning Engineer
Required CredentialsBachelor's or higher in CS, AI, or related; experience with generative modelsBachelor's or higher in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentCollaborates on AI model development, focuses on generative models like GPT, GANsDevelops and deploys ML models for various applications, including predictive analytics
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, and data-driven industries

While both roles involve AI and machine learning, a Remote Generative Ai Engineer specializes in creating models that generate content, such as text or images, using generative techniques. In contrast, a Remote Machine Learning Engineer works on a broader range of ML models for predictive or classification tasks. The roles often overlap but differ in focus and application.

What are the key skills and qualifications needed to thrive as a remote generative AI engineer?

To thrive as a Remote Generative AI Engineer, you need a solid background in computer science, machine learning, and deep learning, typically with a relevant degree and experience in building AI models. Familiarity with frameworks like TensorFlow or PyTorch, cloud platforms (such as AWS or Azure), and version control systems like Git is essential. Strong problem-solving, self-motivation, and effective remote communication set outstanding engineers apart in this role. These skills are crucial for developing innovative AI solutions, collaborating across distributed teams, and delivering impactful results in a remote work environment.

How do remote generative AI engineers typically collaborate with cross-functional teams to deliver AI-driven solutions?

Remote Generative AI Engineers often work closely with data scientists, product managers, and software engineers to integrate generative AI models into products or services. Collaboration is usually facilitated through virtual meetings, code repositories, and project management tools, enabling seamless communication across different time zones. Regular check-ins and sprint reviews help ensure alignment on goals, while documentation and clear communication are essential for maintaining project momentum. This collaborative environment not only fosters innovation but also allows engineers to gain exposure to a variety of perspectives and expertise.

What is a remote generative AI engineer?

A Remote Generative AI Engineer is a technology professional who specializes in developing, training, and deploying artificial intelligence models that can generate new content—such as text, images, audio, or video—while working from a remote location. These engineers typically work with advanced machine learning techniques like deep learning, neural networks, and large language models. Their responsibilities often include designing algorithms, optimizing model performance, and collaborating with distributed teams to build innovative AI-driven solutions. The remote aspect allows them to perform their duties from anywhere with internet access, offering flexibility and access to global opportunities.
What are popular job titles related to Remote Generative Ai Engineer jobs in Silver Spring, MD? For Remote Generative Ai Engineer jobs in Silver Spring, MD, the most frequently searched job titles are:
What job categories do people searching Remote Generative Ai Engineer jobs in Silver Spring, MD look for? The top searched job categories for Remote Generative Ai Engineer jobs in Silver Spring, MD are:
What cities near Silver Spring, MD are hiring for Remote Generative Ai Engineer jobs? Cities near Silver Spring, MD with the most Remote Generative Ai Engineer job openings:
Remote Generative Ai Engineer jobs near you
Infographic showing various Remote Generative Ai Engineer job openings in Silver Spring, MD as of June 2026, with employment types broken down into 100% Full Time. Highlights an 100% Remote job distribution, with an average salary of $119,778 per year, or $57.6 per hour.

GenAI Engineer

Phoenix Oversight Group LLC

Arlington, VA • Remote

Full-time

Re-posted 8 days ago

Job description

Salary: $60,000-$130,000

PhoenixTeam is aremote-firstorganization and applicants for this position can work from anywhere within the US.


Role Overview

Were looking for a hands-on, execution-oriented GenAI Engineer to help design, implement, and scale generative AI solutions across real client environments.


This is not a purely research role and not a narrow model tinkering role either. Youll operate at the intersection ofapplied AI engineering, client delivery, and internal capability building, turning promising GenAI concepts into reliable, production-ready solutions.


Youll work closely with Value Engineers, clients, and internal stakeholders to match the right models and architectures to real business problems especially in regulated, high-stakes environments. This role is ideal for someone who enjoys ownership, thrives in ambiguity, and wants to see their work move from prototype to production.


What Youll Do

  • Applied AI Engineering & Delivery
  • Design, implement, fine-tune, and deploy generative AI and ML solutions aligned to real business use cases.
  • Translate technical and business requirements into scalable AI architectures and implementation plans.
  • Lead or support end-to-end AI solution delivery, from experimentation through deployment and iteration.
  • Serve as the primary technical voice on GenAI initiatives, ensuring clarity across technical and non-technical stakeholders.
  • Model Selection, Tuning & Scaling
  • Evaluate and apply appropriate models (e.g., GPT-based LLMs, BERT-style architectures, or other approaches) based on problem context.
  • Fine-tune, integrate, and operationalize models with support from specialized teammates when needed.
  • Contribute to decisions around model performance, cost, latency, and reliability tradeoffs.
  • Support early MLOps practices, including deployment patterns, monitoring, and iteration.
  • Collaboration & Enablement
  • Partner closely with Value Engineers, product leaders, and clients to align AI solutions with business goals.
  • Communicate complex technical concepts clearly to non-technical audiences.
  • Contribute to internal knowledge sharing, patterns, and best practices for GenAI delivery.
  • Mentor teammates and support PhoenixTeam learning and growth initiatives.
  • Continuous Learning & Innovation
  • Stay current on emerging GenAI techniques, tools, and platforms.
  • Experiment with new approaches and bring practical insights back to the team.
  • Support PhoenixTeams evolution in AI delivery methods, tooling, and ways of working.

What You Bring

  • Must-Have:
  • Bachelors or Masters degree in Computer Science, AI, Machine Learning, or a related field.
  • Experience delivering technical projects that involve collaboration across stakeholders with varying technical depth.
  • Hands-on familiarity with generative AI concepts (e.g., LLMs, fine-tuning, embeddings) and a strong desire to deepen expertise.
  • Experience deploying or working with models on cloud platforms (AWS, Azure, or GCP).
  • Strong communication skills you can explain why and how, not just what.
  • Ability to take ownership, manage priorities, and deliver outcomes in fast-moving environments.
  • Nice-to-Have:
  • Exposure to MLOps practices, containerization, or model monitoring.
  • Experience with AI/NLP applications beyond basic experimentation.
  • Familiarity with AI evaluation methods and performance metrics.
  • Interest in ethical AI, governance, and data security principles.
  • Experience in regulated industries (a plus, not a blocker).

What Success Looks Like:

  • Delivery Excellence: You produce polished, high-quality work and take ownership of outcomes not just tasks.
  • Leadership & Resilience: You lead through influence, adapt quickly, and help teams stay aligned when things change.
  • Teamwork: Youre a generous collaborator who adds value, shares knowledge, and steps in when help is needed.
  • Client Mindset: You care deeply about client outcomes and build trust through clarity, empathy, and follow-through.
  • Learning Champion: Youre curious, self-directed, and committed to continuous growth.
  • Mentor & Coach: You support others through feedback, guidance, and shared problem-solving.
  • Operational Excellence & Innovation: You help improve how PhoenixTeam works from internal processes to communities of practice.