Machine Learning Engineer

About RAD

RAD Intel is building the future of AI-powered growth. We’re a fast-scaling company backed by 10,000+ investors and $50M+ raised, with a mission to reinvent how businesses grow through our AIBO (Artificial Intelligence Buy-Out) strategy. RAD acquires and partners with agencies, clinics, and real-economy businesses, then infuses them with our proprietary AI marketing and operations platform to unlock compounding value. With a team of entrepreneurs, operators, and technologists, we’re driving one of the most ambitious AI strategies in the market—democratizing access to world-class AI tools while creating investor-grade outcomes at scale.

About the Role

We’re seeking a Machine Learning Engineer who thrives at the intersection of software development and applied ML. In this role, you’ll update and extend AI-powered features across multiple pipelines, with a focus on building conversational agents and multi-agent systems. Your experience in software development will be applied in code optimization and application development.

Key Responsibilities

• Collaborate with cross-functional teams on conversational AI and other chat bot related tools and LLM integrations.

• Work closely with the NLP team to release our own in-house LLMs.

• Support in building agent-based automation systems that power our chat bot systems and complete integration with our in-house LLMs.

• Build, test, optimize and deploy software components across our ML pipelines while also updating existing AI features with state-of-the-art models.

• Maintain robust infrastructure for data ingestion and fine tuning / re-training models.

• Stay current on advancements in generative content and advise / inform the team on updating our models / feature space.

About You

• Must Have:

  • 1–2 years of experience in software engineering.

  • At least 3 years of experience in ML engineering.

  • Experience in using python based application frameworks such as Flask and FastAPI.

  • Familiarity with Model Context Protocol (MCP) schema design, prompt engineering and orchestration frameworks (e.g., LangChain, LangGraph, etc.)

  • Familiarity with agent frameworks and distributed task coordination.

  • Proficiency in Python and experience with ML tools (e.g., scikit-learn, Hugging Face, etc.).

  • Understanding of ML operations and experiment tracking tools.

• Nice-to-have:

  • Masters’ or PhD in a relevant field.

  • Curiosity about LLMs and their focus in real-world applications such as social media based marketing campaigns.

  • Experience with data streaming and real-time analysis is a plus.

What We Offer

• Collaborative, high-energy culture where your voice is heard

• Competitive compensation

• Comprehensive benefits (health, dental, vision, life insurance)

• Stock options — be an owner in our fast-growing startup

• Remote-flexible environment with a strong async culture