AI Engineer

If you’re excited about shaping how AI is built, scaled, and delivered, this is the place for you.\n\nWhy You? Why Now?\nGenerative AI is moving fast—from experimentation to enterprise adoption. We need engineers who can bridge research and production, build reliable ML pipelines, and turn GenAI breakthroughs into real business outcomes.

This role is perfect for someone who enjoys ownership, experimentation, and solving complex problems end to end.\n\nWhat You’ll Do (Key Responsibilities)\n\nFirst 30 Days: Foundation & Immersion\nUnderstand goML’s ML and GenAI platforms, use cases, and architecture\nGet familiar with existing training, inference, and deployment pipelines\nStudy current approaches to RAG, LLM fine-tuning, and model evaluation\nCollaborate with senior engineers and product teams to understand business problems\n\nFirst 60 Days: Build & Experiment\nDesign and develop Generative AI solutions using techniques like RAG, transformers, and LLM-based architectures\nFine-tune pre-trained LLMs for domain-specific and task-specific use cases\nBuild and maintain data pipelines for training and inference workflows\nApply strong software engineering practices to ML and GenAI pipelines\nEvaluate, analyze, and benchmark model performance and quality\nDevelop and deploy proof-of-concept GenAI systems\n\nFirst 180 Days: Ownership & Scale\nOwn end-to-end ML/GenAI pipelines—from training to production deployment\nImplement model optimization and compression techniques where applicable\nProductionize ML and GenAI research for real-world enterprise use cases\nMonitor deployed models and continuously improve performance and reliability\nStay current with advancements in Generative AI and apply them thoughtfully\nCollaborate cross-functionally to solve challenging business problems at scale\n\nWhat You Bring (Qualifications & Skills)\nMust-Have\nBachelor’s or Master’s degree in Computer Science, Machine Learning, AI, or a related field\n3+ years of experience in Generative AI, Machine Learning, or related domains\nStrong programming skills in Python\nHands-on experience with RAG and LLM-based architectures\nExperience building data pipelines, deploying ML/GenAI models, and maintaining them in production\nSolid understanding of ML/GenAI evaluation techniques\nProficiency with Git, Docker, and Linux-based systems\nExperience working with cloud platforms, especially AWS ML/GenAI services\n\nNice-to-Have\nExposure to model compression and optimization techniques\nExperience with popular ML/GenAI frameworks and tools\nFamiliarity with MLOps practices and monitoring systems\nExperience working in fast-paced startup environments\n\nWho You Are\nA strong problem-solver with a research-driven yet pragmatic mindset\nComfortable working independently and collaboratively\nMethodical, detail-oriented, and thoughtful in planning and execution\nA clear communicator who can explain complex ideas simply\n\nWhy Work With Us?\nBe part of a core team building next-gen ML & GenAI platforms\nWork on real enterprise problems, not just experiments\nHigh ownership, rapid learning, and strong growth opportunities\nRemote-first, with opportunities for in-person collaboration\nA culture built around curiosity, hustle, and impact