Full-Time Senior AI Engineer
AppOmni is hiring a remote Full-Time Senior AI Engineer. The career level for this job opening is Senior Manager and is accepting USA based applicants remotely. Read complete job description before applying.
AppOmni
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About The RoleWe are seeking a talented and motivated Senior AI Engineer to join our team and play a key role in the company’s AI strategy. This role offers the opportunity to make a meaningful impact across the whole platform. You will collaborate closely with Product, Engineering, and Field teams to implement different AI applications.
What You’ll Do
Your contributions will focus on data exploration, data science, data analytics, and backend code. The data analytics will include statistical analysis as well as different machine learning algorithms (supervised and unsupervised) and Generative AI.
- Design and develop models: Use tools like Langchain, Scipy, Pandas, scitkit-learn, PySpark, TensorFlow, Keras, and PyTorch to create scalable models that drive automation and insights.
- Build the backend necessary to handle the AI pipeline: this will include the specific AI code and other Python code as needed.
- Build data pipelines: Handle large datasets to ensure data is processed and ready for model training and collaborate in the platform data pipeline.
- Select and implement algorithms: Choose the right algorithm for the problem and data at hand.
- Identifying patterns and correlations: Use data modeling and evaluation skills to predict properties of new instances.
- Research and develop solutions: Use data-driven solutions to address complex business problems.
- Analyze and interpret data: Assess and interpret data to gain insights.
- Clean, preprocess, and extract features: Learn how to handle missing values, normalize data, and select the most relevant features.
- Evaluate and test: Develop metrics to assess the performance of models and generated content, including subjective and objective measurables.
- GenerativeAI: Implement GenAI (LLM) where applicable including choosing models, defining prompt, and examples.
- Integration with applications: Integrate Machine Learning and generative AI models into existing systems.
- Translate stakeholder requirements into technical solutions: Understand the requirements of stakeholders and translate them into technical solutions.