Senior / Intermediate Machine Learning Engineer

You’re the hero we’re looking for if:

• Proficiency in a wide range of machine learning algorithms, including supervised, unsupervised, and reinforcement learning, understanding when and how to apply each specific algorithm.
• Knowledge of data preprocessing techniques, including data cleaning and feature engineering.
• Ability to assess model performance using metrics like accuracy, precision, recall, F1-score, and AUC-ROC, and perform hyperparameter tuning to improve model performance.
• Experience in deploying machine learning models to production environments, including containerization (e.g., Docker) and orchestration tools (e.g., Kubernetes), for batch and real-time inference.
• Familiarity with cloud platforms like AWS, Azure, or Google Cloud for scalable and cost-effective model deployment and data storage.
• Strong programming skills in Python and comfortable with common ML libraries like TensorFlow, PyTorch, scikit-learn, and Keras.
• Strong software engineering principles, including modular code design, code optimization, and familiarity with software development best practices.
• Proficiency in working with databases, both SQL and NoSQL, to access and manipulate data.
• Knowledge of testing frameworks and practices to ensure model performance and reliability in production.
• Strong English communication (both verbal and written)

Nice to have skills/ experiences (but not required to be considered):

• DevOps practices and tools for reliable and scalable data solutions.
• Experience with Generative AI and libraries like LangChain and LlamaIndex
• Familiarity with NLP libraries and frameworks like NLTK, spaCy, Gensim, and Hugging Face Transformers for various NLP tasks.

Experience is important, but for us the biggest measure of success is people who can live and breathe our values. Show us what you can bring to the table, and we’ll empower you to let your talents shine.