AI/ML Engineer

Role impact

• You will convert AI ideas into reliable business features that reduce manual work, improve customer support, and help teams make faster decisions.

Responsibilities

• Prototype and ship AI workflows using LLM APIs, prompt design, retrieval-augmented generation, and structured outputs.
• Prepare datasets, clean source documents, design evaluation criteria, and improve output reliability over iterations.
• Integrate AI features into web applications with backend engineers, including APIs, logs, feedback loops, and fallback states.
• Build automation for content generation, lead qualification, support replies, knowledge search, and internal productivity.
• Document model limitations, privacy considerations, cost tradeoffs, and monitoring requirements for production use.

Required skills

• Strong Python fundamentals and experience building at least one AI, ML, automation, or LLM-based project.
• Understanding of prompts, embeddings, vector search, RAG concepts, JSON outputs, and API-based AI products.
• Ability to evaluate AI output quality, reduce hallucination risk, and design useful human-review workflows.
• Comfort working with documents, APIs, data preprocessing, experiments, and measurable acceptance criteria.
• Clear communication about tradeoffs, limitations, and technical decisions.

Good to have

• LangChain-style orchestration, vector databases, OpenAI/Gemini/Groq APIs, or local model experimentation.
• Experience with OCR, document parsing, semantic search, agents, or workflow automation.
• Basic Next.js or Node.js integration experience.
• Knowledge of privacy, security, and responsible AI practices.

Hiring process

1. 1Application and resume screening by the hiring team.
2. 2Technical or portfolio discussion focused on real project experience.
3. 3Role-specific practical task or work-sample review when required.
4. 4Final alignment on compensation, joining date, and onboarding plan.