Machine Learning Engineer • Senior

Who you are

You have over 4 years of experience as a machine learning engineer, with a strong proficiency in Python and its associated libraries for machine learning, including TensorFlow, PyTorch, Keras, and Scikit-learn. Your background includes working with data manipulation libraries such as Pandas and NumPy, which you use to preprocess and analyze large datasets effectively. You are familiar with generative AI model development and integration, leveraging advanced language models like GPT-3.5, GPT-4, and custom transformer-based models for various generative tasks.

You possess a solid understanding of deep learning frameworks and neural network architectures, including CNNs, RNNs, LSTMs, GANs, and Transformers. Your experience extends to deploying and scaling deep learning models using cloud platforms such as AWS SageMaker, Google Cloud AI, and Azure ML. You are also knowledgeable about observability tools like Langsmith and Weights and Biases, which you use to monitor model behavior and fine-tune applications in production.

Your expertise includes LLMOps practices, where you utilize version control systems like Git and implement CI/CD pipelines for AI model deployment. You have experience with data engineering, including building data pipelines and working with big data technologies such as Hadoop and Spark. You are comfortable with containerization using Docker and orchestration with Kubernetes, ensuring smooth deployment processes for AI applications.

You are a proactive problem solver who enjoys collaborating with cross-functional teams to drive innovation in AI and machine learning. You have a passion for staying updated with the latest advancements in the field and are eager to apply your knowledge to real-world challenges.

Desirable

Experience with additional programming languages or tools is a plus, as is familiarity with experiment tracking tools like MLflow and Kubeflow. You may also have insights into the latest trends in generative AI and its applications across various industries.

What you'll do

In this role, you will design and develop generative AI models, focusing on tasks such as text generation, summarization, and question-answering. You will leverage advanced language models and frameworks like Langchain to create applications that require complex prompt chains and integration with external APIs for data retrieval. Your responsibilities will include deploying and scaling these models on cloud platforms, ensuring they perform optimally in production environments.

You will set up observability tools to monitor model performance, understand errors, and implement necessary adjustments to enhance application functionality. Collaborating closely with data engineers and other stakeholders, you will contribute to building robust data pipelines and preprocessing techniques that support large-scale datasets.

Your role will also involve implementing best practices in LLMOps, including version control and CI/CD pipelines, to streamline the deployment of AI models. You will participate in code reviews and mentor junior engineers, fostering a collaborative and innovative team environment.

What we offer

At Emids, you will be part of a dynamic team that is at the forefront of AI and machine learning technology. We offer a competitive salary and benefits package, along with opportunities for professional growth and development. You will work in a hybrid environment, allowing for flexibility while collaborating with talented professionals in the field. Join us to make a significant impact in the world of generative AI and machine learning.