AI Software Engineer Consultant

Job Title

AI Software Engineer Consultant (Part-Time, Remote – Open Source AI Integration)

Job Brief

Mayan Solutions, Inc. is seeking a highly skilled AI Software Engineer Consultant to help integrate open-source AI models into our on-premise software and automation systems. This is a part-time, fully remote consulting role for an experienced software engineer with strong machine learning foundations and a passion for bringing AI features to life within enterprise software.

You will lead the design and implementation of AI-powered capabilities such as text classification, chatbots, natural language understanding (NLU), and voice query processing. Beyond model selection, you'll architect how these models integrate into backend services, expose them via APIs, and ensure smooth deployment on self-hosted infrastructure.

This role is ideal for an ML-focused backend engineer who understands both sides of AI and software delivery, someone who can fine-tune models and also make them production-ready. You'll collaborate closely with Mayan's engineering and product teams to transform our client solutions into intelligent, scalable systems that deliver measurable impact.

Core Responsibilities

• Select, fine-tune, and deploy open-source AI models (e.g., LLaMA, Whisper, DistilBERT, RoBERTa) that power features such as chatbots, text classification, and voice recognition.
• Build and expose REST APIs that serve model predictions to software systems.
• Define and document how AI models integrate with business logic, databases, and user interfaces across the software stack.
• Configure and deploy models on on-premises servers using Docker or Kubernetes, ensuring optimal performance, scalability, and resource efficiency.
• Monitor inference performance, tune hardware utilization (CPU/GPU), and optimize response latency and throughput.
• Work closely with backend and product engineers to ensure AI components align with business goals and existing architecture.
• Produce clear technical documentation for model pipelines, APIs, and deployment processes.
• Advise on infrastructure and tooling choices (e.g., GPU utilization, vector databases, MLOps workflows).

Day-to-Day Activities

• Experiment with and fine-tune AI models to match system requirements.
• Containerize and deploy inference services using Docker/Kubernetes.
• Build backend endpoints that connect AI logic with software workflows.
• Collaborate with the dev team to integrate AI outputs into user-facing systems.
• Optimize model performance and troubleshoot deployment issues.
• Monitor logs, track metrics, and adjust configurations for stability and speed.
• Stay up to date with open-source model advancements (e.g., LLaMA, Mistral, Whisper updates).

Requirements and Skills

• 3+ years of experience in software engineering with a focus on AI or machine learning.
• Proficient in Python and frameworks such as PyTorch or TensorFlow.
• Hands-on experience deploying open-source models locally or on-prem (not just via cloud APIs).
• Strong background in backend development, including RESTful API design and integration.
• Proficiency in Docker and familiarity with Kubernetes for managing inference workloads.
• Experience working with transformer-based models (e.g., BERT, LLaMA, Whisper, Flan-T5).
• Familiarity with vector databases, embeddings, and retrieval-augmented generation (RAG).
• Strong debugging, optimization, and performance tuning skills for GPU/CPU workloads.
• Excellent written and verbal communication; capable of working independently in a remote setup.
• Bachelor's degree or higher in Computer Science, Data Science, or related field (or equivalent practical experience).

Preferred Experience

• Prior experience building or integrating AI features into enterprise systems.
• Familiarity with NLU, speech-to-text, and chatbot architectures.
• Experience with MLOps tools (e.g., MLflow, DVC, or Kubeflow).
• Contributions to open-source ML frameworks or projects.
• Experience working with containerized AI inference pipelines in on-prem or hybrid environments.
• Understanding of data privacy and security in self-hosted AI environments.

Job Types: Part-time, Fixed term

Contract length: 3 months

Expected hours: No more than 40 per week

Application Question(s):

• Do you have experience in using AI APIs and deploying open source AI models for local use?
• Do you have experience in fine-tuning to improve the performance of AI models?

Willingness to travel:

• 25% (Required)

Work Location: Remote