Machine Learning Engineer

Build the Future of Generative AI with goML
At goML, we’re building the next generation of Machine Learning platforms and Generative AI services that solve real-world enterprise problems. We work at the intersection of cutting-edge research and production-grade engineering—turning ideas into scalable, impactful AI systems.
We’re looking for a Generative AI / Machine Learning Engineer to join our core team of young hustlers. In this role, you’ll design, build, and product ionize GenAI systems—from model training and fine-tuning to deployment and monitoring. If you’re excited about shaping how AI is built, scaled, and delivered, this is the place for you.

Why You? Why Now?
Generative 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.

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

First 60 Days:
Build & Experiment
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

First 180 Days:
Ownership & Scale
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

What You Bring (Qualifications & Skills)
Must-Have
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

Nice-to-Have
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

Who You Are
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

Why Work With Us?
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