Machine Learning Engineer • Senior

Who you are

You have 5-7 years of experience in software engineering with a strong focus on AI and machine learning. Proficiency in Python and its ML libraries such as TensorFlow, PyTorch, Keras, and Scikit-learn is essential. You are familiar with data manipulation libraries like Pandas and NumPy, and you have experience in designing and developing generative AI models using language models like GPT-3.5, GPT-4, and custom Transformer-based models.

Your experience extends to deploying and scaling deep learning and generative AI models using cloud platforms such as AWS SageMaker, Google Cloud AI, and Azure ML. You have a solid understanding of observability tools and can monitor model behavior, understand errors, and fine-tune applications in production. You are also knowledgeable about LLMOps practices, including version control with Git and CI/CD pipelines for AI models.

You possess a strong understanding of deep learning frameworks and neural network architectures, including CNNs, RNNs, LSTMs, GANs, and Transformers. Your background includes working with data pipelines, data preprocessing techniques, and large-scale datasets. Familiarity with big data technologies like Hadoop and Spark, as well as containerization with Docker and orchestration with Kubernetes, is a plus.

What you'll do

In this role, you will leverage your expertise to design and develop generative AI models for various applications, including text generation, summarization, and chatbots. You will utilize frameworks like Langchain to develop applications that require complex chains of prompts and manage multiple LLM calls. Your responsibilities will include deploying and scaling models on cloud platforms, ensuring they are robust and efficient.

You will set up observability tools in generative AI applications, monitor model performance, and make necessary adjustments to improve accuracy and efficiency. Collaborating with cross-functional teams, you will contribute to the development of innovative AI solutions that meet business needs.

You will also be involved in implementing best practices for LLMOps, including experiment tracking with tools like MLflow and Kubeflow. Your role will require you to stay updated with the latest advancements in AI and machine learning, ensuring that the solutions you develop are cutting-edge and effective.

What we offer

At Emids, we provide a collaborative and innovative work environment where you can thrive. We encourage you to apply even if your experience doesn't match every requirement. You will have the opportunity to work on impactful projects that leverage the latest technologies in AI and machine learning. We offer competitive compensation and benefits, along with opportunities for professional growth and development in a rapidly evolving field.