Role overview
We are seeking a highly adaptable, creative, and well-rounded Machine Learning Engineer to join our team. You will own the end-to-end ML lifecycle, from dataset creation and foundational research to building and deploying production-grade models. If you thrive in an environment where you can quickly iterate, experiment with cutting-edge techniques, and see your work make a tangible impact, this is the role for you.
What you'll work on
- Proven experience (3+ years) in building, training, and deploying machine learning models in a production environment.
- Expert-level proficiency in Python
- Experience with modern deep learning frameworks, such as PyTorch.
- Demonstrable experience with systematic hyperparameter searching and optimization frameworks (e.g., Optuna, Ray Tune).
- Exceptional organizational skills, with a strong emphasis on reproducible research and methodical experiment tracking.
- Direct experience with LLMs, including fine-tuning, prompt engineering, RAG, and efficient inference.
- Practical experience implementing model optimization techniques like quantization (e.g., bitsandbytes) and pruning
- Experience in designing and curating novel datasets from scratch.
- Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related technical field.
What we're looking for
- Familiarity with advanced model architectures like Transformers and Mixtures of Experts (MoE).
- Contributions to open-source ML projects or a portfolio of personal projects demonstrating a passion for the field.
- Strong, hands-on understanding of the MLOps lifecycle and associated tools (e.g., Docker, Kubernetes, MLflow, Kubeflow, Prometheus).
If this sounds like you, we'd love to have a chat!
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Ai Machine Learning