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Stevens

engineering opportunity

AI / ML Engineer - Hourly Contract

Design and build production-grade AI and machine learning systems, including LLM-powered applications and agentic workflows. Collaborate with delivery pods to integrate AI capabilities into complex enterprise systems while ensuring reliability, scalability, and performance.

United StatesremoteCONTRACTOR

Posted

About the role

What will you do at Stevens?

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.

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.

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.

Which skills does this role require?

PythonRAGRetrieval systemsAgentic workflowsAPI developmentCloud computingGoogle CloudSoftware architectureDistributed systemsProduction engineeringSystem evaluationMLAPISemantic searchEmbeddingsEnterprise systemsEvaluation frameworksLatency optimizationScalabilityTechnical planningCode reviews1099 contractorGCPLLMsPrototyping

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