Senior Machine Learning Engineer

Required skills

5+ years of experience in Machine Learning Engineering, with a proven track record of deploying models into production environments. Expert proficiency in Python and standard ML libraries (PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy). Strong experience with transformer architectures (BERT, GPT, Llama) and NLP frameworks (Hugging Face, LangChain). Proficiency with MLOps tools and practices, including containerization (Docker), orchestration (Kubernetes), and experiment tracking (MLflow). Ability to design data preprocessing pipelines for both structured (SQL, tabular) and unstructured (text, PDF) data. Strong grasp of algorithmic principles for implementing custom logic, such as graph traversal or geometric computations. Ability to quickly learn and apply ML techniques to specialized domains like engineering, supply chain, or other highly regulated industries. Experience working in agile environments (Sprints) while adhering to rigorous engineering standards and documentation requirements. Strong communication skills to work effectively with Data Scientists, Backend Engineers, and Domain Experts to align technical solutions with business needs.

Preferred skills

Technologies

Docker, Kubernetes, Kubeflow, MLflow, PyTorch, TensorFlow, Scikit-learn, Pandas, NumPy, BERT, GPT, Llama, Hugging Face, LangChain, SQL, tabular data, text, PDF, Python

Responsibilities

LLM and NLP Pipelines, Predictive and Analytical Models (Supply Chain), MLOps and Productionization

Seniority

Senior

Domain

AI/ML, NLP, Predictive Analytics, Supply Chain, Compliance, Engineering