About the role
What You’ll Do (Key Responsibilities)First 30 Days: Foundation & Immersion
- Understand goML’s ML and GenAI platforms, use cases, and architecture
- Get familiar with existing training, inference, and deployment pipelines
- Study current approaches to RAG, LLM fine-tuning, and model evaluation
- Collaborate with senior engineers and product teams to understand business problems
- Design and develop Generative AI solutions using techniques like RAG, transformers, and LLM-based architectures
- Fine-tune pre-trained LLMs for domain-specific and task-specific use cases
- Build and maintain data pipelines for training and inference workflows
- Apply strong software engineering practices to ML and GenAI pipelines
- Evaluate, analyze, and benchmark model performance and quality
- Develop and deploy proof-of-concept GenAI systems
- Own end-to-end ML/GenAI pipelines—from training to production deployment
- Implement model optimization and compression techniques where applicable
- Productionize ML and GenAI research for real-world enterprise use cases
- Monitor deployed models and continuously improve performance and reliability
- Stay current with advancements in Generative AI and apply them thoughtfully
- Collaborate cross-functionally to solve challenging business problems at scale
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, AI, or a related field
- 3–5 years of experience in Generative AI, Machine Learning, or related domains
- Strong programming skills in Python
- Hands-on experience with RAG and LLM-based architectures
- Experience building data pipelines, deploying ML/GenAI models, and maintaining them in production
- Solid understanding of ML/GenAI evaluation techniques
- Proficiency with Git, Docker, and Linux-based systems
- Experience working with cloud platforms, especially AWS ML/GenAI services
- Exposure to model compression and optimization techniques
- Experience with popular ML/GenAI frameworks and tools
- Familiarity with MLOps practices and monitoring systems
- Experience working in fast-paced startup environments
- A strong problem-solver with a research-driven yet pragmatic mindset
- Comfortable working independently and collaboratively
- Methodical, detail-oriented, and thoughtful in planning and execution
- A clear communicator who can explain complex ideas simply
- Be part of a core team building next-gen ML & GenAI platforms
- Work on real enterprise problems, not just experiments
- High ownership, rapid learning, and strong growth opportunities
- Remote-first, with opportunities for in-person collaboration
- A culture built around curiosity, hustle, and impact