Job Description:
Machine Learning / AI Engineer (with 3+ years of experience)
We are seeking a highly skilled and passionate Machine Learning / AI Engineer to join our newly established data science practice area. In this role, you will primarily focus on working with Large Language Models (LLMs) and contribute to building generative AI applications. This position offers an exciting opportunity to shape the future of AI technology while charting an interesting career path within our organization.
Responsibilities:
1. Develop and implement machine learning models: Utilize your expertise in machine learning and artificial intelligence to design, develop, and deploy cutting-edge models, with a particular emphasis on Large Language Models (LLMs). Apply your knowledge to solve complex problems and optimize performance.
2. Building generative AI applications: Collaborate with cross-functional teams to conceptualize, design, and build innovative generative AI applications. Work on projects that push the boundaries of AI technology and deliver impactful solutions to real-world problems.
3. Data preprocessing and analysis: Collect, clean, and preprocess large volumes of data for training and evaluation purposes. Conduct exploratory data analysis to gain insights and identify patterns that can enhance the performance of AI models.
4. Model training and evaluation: Develop robust training pipelines for machine learning models, incorporating best practices in model selection, feature engineering, and hyperparameter tuning. Evaluate model performance using appropriate metrics and iterate on the models to improve accuracy and efficiency.
5. Research and stay up to date: Keep abreast of the latest advancements in machine learning, natural language processing, and generative AI. Stay informed about industry trends, emerging techniques, and open-source libraries, and apply relevant findings to enhance the team's capabilities.
6. Collaborate and communicate effectively: Work closely with a multidisciplinary team of data scientists, software engineers, and domain experts to drive AI initiatives. Clearly communicate complex technical concepts and findings to both technical and non-technical stakeholders.
7. Experimentation and prototyping: Explore novel ideas, experiment with new algorithms, and prototype innovative solutions. Foster a culture of innovation and contribute to the continuous improvement of AI methodologies and practices within the organization.
Requirements:
1. Education: Bachelor's or Master's degree in Computer Science, Data Science, or a related field. Relevant certifications in machine learning, deep learning, or AI are a plus.
2. Experience: A minimum of 3+ years of professional experience as a Machine Learning / AI Engineer, with a proven track record of developing and deploying machine learning models in real-world applications.
3. Strong programming skills: Proficiency in Python and experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn, pandas). Experience with cloud platforms (e.g., AWS, Azure, GCP) for model deployment is preferred.
4. Deep-learning expertise: Strong understanding of deep learning architectures (e.g., convolutional neural networks, recurrent neural networks, transformers) and familiarity with Large Language Models (LLMs) such as GPT-3, GPT-4, or equivalent.
5. Natural Language Processing (NLP) knowledge: Familiarity with NLP techniques, including tokenization, word embeddings, named entity recognition, sentiment analysis, text classification, and language generation.
6. Data manipulation and preprocessing skills: Proficiency in data manipulation using SQL and experience with data preprocessing techniques (e.g., cleaning, normalization, feature engineering). Familiarity with big data tools (e.g., Spark) is a plus.
7. Problem-solving and analytical thinking: Strong analytical and problem-solving abilities, with a keen eye for detail. Demonstrated experience in translating complex business requirements into practical machine learning solutions.
8. Communication and collaboration: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to diverse stakeholders
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