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