Founding Machine Learning Engineer

We are looking for a highly driven Founding AI / ML Engineer to build and scale cutting-edge AI systems from the ground up. This role is ideal for someone who thrives in fast-moving startup environments, enjoys solving ambiguous problems, and wants to shape both the product and the engineering culture from day one. You will work closely with the founders to architect, develop, and deploy AI-powered products leveraging LLMs, NLP, computer vision, and agentic AI systems.
Responsibilities:
Design, prototype, and deploy machine learning models across NLP, LLMs, and computer vision use cases from concept to production.
Build scalable data pipelines, model-serving infrastructure, and monitoring systems from scratch.
Set up and manage CI/CD pipelines, model versioning systems, retraining workflows, and cloud infrastructure.
Establish engineering best practices and coding standards and help define the company's long-term technical foundation.
Optimize AI systems for performance, latency, scalability, and cost efficiency.
Collaborate closely with founders on product direction, technical strategy, and execution priorities.
Experiment with emerging AI technologies, including RAG pipelines, autonomous agents, and generative AI architectures.
Requirements:
Skills and Technologies: Machine Learning, Agentic AI CI/CD Computer Vision, Generative AI LLMs NLP Python PyTorch Scikit-learn SQL TensorFlow.
5+ years of experience in Machine Learning Engineering with a strong track record of shipping AI/ML products to production.
Strong proficiency in Python and experience with libraries such as Pandas, NumPy, and Scikit-learn.
Hands-on experience with deep learning frameworks including PyTorch, TensorFlow, and JAX.
Strong understanding of data engineering, SQL, and large-scale data processing.
Experience building and deploying scalable ML infrastructure and production-grade AI systems.
Ability to work effectively in ambiguous, high-speed startup environments with a bias toward execution and iteration.
Familiarity with LLMs, RAG pipelines, agentic workflows, or autonomous AI architectures.
Strong problem-solving skills and ownership mindset.
Preferred Qualifications:
Experience working in an early-stage startup or building products from scratch.
Exposure to cloud platforms such as AWS, GCP, or Azure.
Experience with MLOps tooling, observability, and distributed systems.
Passion for emerging AI technologies and practical product innovation.

Experience
5-9 yrs