AI / ML Engineer - Hourly Contract

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 s…