AI Engineer

Job not on LinkedIn

February 11

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i1x

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i1x is not for the faint of heart.

11 - 50 employees

Founded 2022

📋 Description

• Work closely with the engineering, product, and data teams to integrate machine learning models and AI-powered features into our platform. • Design AI systems, training models, and deploying them at scale on cloud infrastructure. • Design, build, and deploy AI/ML models that solve real-world problems, including recommendation systems, predictive analytics, and natural language processing (NLP) solutions. • Collaborate with product managers and stakeholders to identify AI opportunities that align with business objectives. • Collect, preprocess, and analyze large datasets to build and train machine learning models. • Implement end-to-end pipelines for deploying AI models, including data collection, feature engineering, model training, and production deployment. • Continuously improve the performance and accuracy of existing models by monitoring them in production and iterating based on user feedback and new data. • Ensure the scalability and reliability of AI systems by optimizing them for performance on cloud platforms such as AWS. • Stay up to date with the latest research and trends in machine learning, deep learning, and AI.

🎯 Requirements

• 3+ years of experience as an AI/Machine Learning Engineer, Data Scientist, or a related role. • Strong proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). • Proven experience designing, training, and deploying machine learning models in a production environment. • Solid understanding of data structures, algorithms, and statistical methods. • Experience with natural language processing (NLP), computer vision, or deep learning models. • Proficiency in Python and familiarity with other programming languages (e.g., Java, C++). • Experience working with cloud platforms like AWS, GCP, or Azure, and deploying AI solutions in a cloud-native environment. • Experience with MLOps best practices, including version control, automated testing, and CI/CD pipelines for machine learning models. • Strong analytical and problem-solving skills, with an ability to work through ambiguity and adapt to a fast-paced startup environment. • Knowledge of tools like Docker and Kubernetes for containerized AI model deployment. • Experience with recommendation systems, time series analysis, or reinforcement learning. • Familiarity with data visualization tools like D3.js, Plotly, or similar libraries. • Understanding of ethical AI and bias reduction techniques in machine learning. • Previous experience working in a startup or small team environment. • Strong collaboration and communication skills, especially when working with cross-functional teams such as product managers and designers. • A proactive attitude: able to take ownership of projects and lead initiatives. • Ability to explain complex AI concepts in simple terms to non-technical stakeholders. • Entrepreneurial mindset with a willingness to experiment and iterate quickly based on user feedback. • Passion for continuous learning and staying ahead in a rapidly evolving field.