AI / ML Engineer - Hourly Contract

Hybrid • Posted 14 hours ago • Updated 14 hours ago
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Hybrid
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Job Details

Skills

  • Active Security Clearance
  • Agentic AI
  • Agentic Workflows
  • AI Agents
  • AI Engineer
  • AI Software Engineer
  • Anthropic
  • Applied AI Engineer
  • Applied Machine Learning Engineer
  • Artificial Intelligence
  • Artificial Intelligence Engineer
  • AWS
  • AWS Bedrock
  • Azure
  • Azure OpenAI
  • Claude
  • Cleared AI Engineer
  • Cleared Engineer
  • Cleared Software Engineer
  • Context Engineering
  • Department of Defense
  • Docker
  • DoD
  • Embeddings
  • FastAPI
  • Federal Government
  • Fine-Tuning
  • Frameworks / tooling LangChain
  • Function Calling
  • GCP
  • Gemini
  • GenAI
  • GenAI Engineer
  • Generative AI
  • Generative AI Engineer
  • Google Vertex AI
  • Government Contractor
  • GPT
  • Hugging Face
  • Kubernetes
  • LangChain
  • LangGraph
  • Large Language Models
  • LlamaIndex
  • LLM
  • LLM Engineer
  • LLM Evaluation
  • LLM Observability
  • Machine Learning
  • Machine Learning Engineer
  • ML Engineer
  • MLflow
  • MLOps
  • Model Deployment
  • Models / platforms OpenAI
  • NLP
  • OpenAI
  • Prompt Engineering
  • Python
  • PyTorch
  • RAG
  • Retrieval Augmented Generation
  • SCI
  • Secret Clearance
  • Security Clearance
  • Semantic Search
  • Senior AI Engineer
  • Senior Machine Learning Engineer
  • Structured Outputs
  • TensorFlow
  • Tool Calling
  • Top Secret
  • Transformers
  • TS
  • TS/SCI
  • US Security Clearance
  • Vector Database
  • Vector Search
  • Vertex AI

Summary

Stevens is a strategic advisory and technology firm that partners with companies on high-impact transformation and technology initiatives. We work closely with executive and technology leaders to solve complex problems, identify opportunities, and turn strategy into working solutions.

We re looking for an experienced AI / ML Engineer to join Stevens on an hourly contract basis and work as part of our delivery teams on enterprise client engagements.

Our AI work goes well beyond prototypes. We build production systems that need to perform reliably inside real businesses. Depending on the engagement, that may include LLM-powered applications, retrieval and knowledge systems, agentic workflows, evaluation infrastructure, machine learning pipelines, or integrating AI capabilities into complex existing systems.

You ll be assigned to a Stevens delivery pod alongside engineers, technical leadership, project management, and client stakeholders. We expect our engineers to take ownership of their work, contribute to technical decisions, and be comfortable operating in demanding enterprise environments.

Depending on the engagement, you will:


  • Design and build production-grade AI and machine learning systems

  • Build applications and services using LLMs and foundation models

  • Develop RAG, semantic search, embeddings, retrieval, and knowledge systems

  • Design agentic and tool-using AI workflows

  • Build backend services, APIs, and integrations supporting AI applications

  • Design evaluation frameworks and systematically measure AI system quality

  • Work with structured and unstructured enterprise data

  • Integrate AI capabilities into existing enterprise applications and systems

  • Evaluate models, architectures, and tooling based on business and technical requirements

  • Optimize AI systems for reliability, latency, scalability, and cost

  • Implement appropriate testing, observability, and production safeguards

  • Participate in architecture discussions, technical planning, and code reviews

  • Collaborate with Stevens architects, engineers, technical project managers, and client teams

  • Own technical work from initial design through production delivery

This role is currently limited to contractors located in the United States.


Requirements



  • Strong professional software engineering experience with the ability to independently own production engineering work

  • Demonstrated experience building and shipping AI, LLM, or machine learning systems in production

  • Strong Python development skills

  • Strong understanding of software architecture, APIs, distributed systems, testing, and production engineering practices

  • Hands-on experience with leading LLMs and foundation model platforms

  • Experience with RAG, embeddings, vector search, semantic retrieval, structured outputs, tool/function calling, and context management

  • Experience designing and evaluating prompts, retrieval strategies, and AI application behavior

  • Understanding of LLM evaluation and methods for systematically measuring output quality

  • Experience integrating AI capabilities into larger applications and enterprise systems

  • Experience deploying and operating production workloads in AWS, Azure, or Google Cloud

  • Familiarity with modern data stores, APIs, queues, caching, and production infrastructure

  • Ability to reason through ambiguous technical problems and make sound engineering decisions

  • Strong written and verbal communication skills

  • Ability to work effectively within a delivery pod and communicate technical decisions to both technical and non-technical stakeholders

  • Ability to participate in client and team meetings during U.S. business hours when required

  • Must be located in the United States and legally authorized to work in the United States

Experience in one or more of the following is a plus:


  • Agentic AI systems and multi-step AI workflows

  • LLM evaluation, observability, safety, and guardrails

  • Fine-tuning or model adaptation

  • PyTorch, TensorFlow, or other machine learning frameworks

  • Traditional machine learning, NLP, computer vision, or multimodal systems

  • Data engineering and large-scale data processing

  • Vector databases and search infrastructure

  • MLOps and model deployment

  • AWS Bedrock, Google Vertex AI, Azure AI, or similar enterprise AI platforms

  • Enterprise security, identity, governance, or compliance

  • Consulting, professional services, or other customer-facing engineering environments

  • An active U.S. government security clearance is a plus, but is not required for this role

You do not need experience with every technology listed above. We place significantly more weight on engineering depth, technical judgment, and demonstrated experience shipping production systems than familiarity with any particular framework.

Candidates may be asked to complete additional technical assessments or screening as part of the selection process. Depending on the engagement, additional technical or client interviews may also be required.


Benefits


This is an hourly independent contractor (1099) position, not a salaried full-time role.


  • Competitive hourly compensation based on experience

  • Remote work within the United States

  • Work on complex, production-grade enterprise AI initiatives

  • Collaborate with experienced engineers, architects, and delivery leaders

  • Exposure to a range of enterprise environments, industries, and technologies

  • Contractors are paid bi-weekly through Deel

  • Hours are logged through Harvest

Hours may vary based on client and project requirements. All contract engagements are subject to successful completion of a standard U.S. criminal background check.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 90891647
  • Position Id: 7C19A85059
  • Posted 14 hours ago
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