HIRE DEVELOPERS / AI/ML DEVELOPERS
AI/ML development is more than calling the OpenAI API. Our developers build production AI systems — LLM applications, RAG pipelines, fine-tuned models, and inference APIs that are monitored, evaluated, and maintained. Real machine learning, not demos.
Our AI/ML developers work across the full stack — LLM integration with OpenAI and Anthropic, RAG systems with Pinecone and pgvector, agent frameworks with LangChain, and traditional ML with PyTorch. We focus on evaluation pipelines and MLOps so models stay reliable in production.
Vetted for production AI — not notebook experiments. RAG architecture, embedding model selection, evaluation frameworks, hallucination detection, and real experience deploying AI features with monitoring and cost controls.
AI developers who call an API are everywhere. AI developers who build eval pipelines, handle retrieval chunking strategy, and deploy with cost monitoring — that pool is small. We keep them ready.
Dedicated developer for a long-term AI product. Part-time specialist for adding LLM features to an existing app. Hourly consultant for a RAG review or cost audit. You choose.
Most "AI developers" know how to call an API and stream a response. Production AI requires evaluation frameworks, observability, cost management, and engineering discipline so systems don't silently mislead users. Our developers treat training, evaluation, and deployment as one system — not three separate experiments.
A dedicated AI/ML developer embedded in your team full-time — building LLM integrations, RAG pipelines, fine-tuning workflows, and production inference APIs. Best for teams building AI as a core product capability.
20 hours per week of focused AI/ML work. Ideal for teams adding LLM features to an existing product, running prompt iterations, building eval datasets, or migrating between model providers.
Targeted AI/ML consulting — RAG architecture design, vector database selection, prompt review, cost analysis, or AI feasibility assessment. Scoped, delivered, done.
Pick the engagement model that fits how your team runs AI/ML work — or talk to us and we'll suggest the right one.
We own delivery end-to-end — AI architecture, model integration, evaluation pipelines, and production deployment. You review weekly and steer the product.
Your engineering lead sets priorities. Our AI/ML developer joins your Slack, your GitHub, your standups. They build AI features, tune prompts — you direct the product.
Your team handles product decisions and frontend. Our AI/ML specialist handles the intelligence layer — prompts, RAG, model serving, evaluation, and cost management.
Full AI/ML stack from LLM integration to classical machine learning. Here's what our engineers work with daily.
Pipelines, APIs, and model training scripts.
Deep learning training and fine-tuning.
Production ML models and serving graphs.
Classical ML for tabular and baseline models.
RAG chains, agents, and tool orchestration.
Stateful multi-step agent workflows.
Adjacent services we often ship alongside AI/ML work — same bench, same standard.
Six questions we get on every first call about hiring AI/ML developers. If yours isn't here, we'll cover it first.
Discuss your AI/ML needs with Entalogics — quality delivery at fair pricing.
