About fileAI
fileAI leverages proprietary AI to process any file end-to-end directly into any system without manual intervention. By streamlining repetitive workflows, fileAI enables teams to focus on higher-value tasks and boost productivity.
How you'll contribute
- Collaborate with the leadership team to define and articulate the AI vision, strategy, and roadmap, ensuring alignment with overall product and business goals. Identify high-impact opportunities where AI can solve user problems and create significant competitive advantages.
- Act as the primary technical expert for AI within the organization.
- Spend a significant portion of your time directly contributing to the codebase. This includes:
- Designing, building, and optimizing scalable machine learning models, algorithms, and AI systems (e.g., LLMs, NLP, predictive analytics, computer vision, recommendation systems) relevant to our SaaS product.
- Developing and maintaining robust data pipelines for data collection, preprocessing, feature engineering, and model training.
- Implementing and refining AIOps and MLOps practices for seamless model deployment, monitoring, and retraining in production environments. Documenting processes and performance of models for internal and external communication. Prioritize security in all processes.
- Writing clean, efficient, well-documented, and testable code.
- Provide architectural guidance and technical oversight for all AI/ML projects.
- Conduct thorough code reviews, establish best practices, and ensure high code quality.
- Mentor and grow junior and mid-level AI/ML engineers, sharing your expertise and fostering their development.
- Troubleshoot complex technical issues and guide the team through challenging problems.
- Work closely with Product Managers, Frontend, and Backend Engineers to seamlessly integrate AI capabilities into our SaaS platform, ensuring a cohesive and intuitive user experience. Participate actively in product design and feature definition.
- Collaborate with data teams to ensure the availability of high-quality data, establish data governance, and define data requirements for effective AI model development and evaluation.
- Champion the development of responsible and ethical AI solutions, considering aspects like fairness, transparency, and data privacy.
Who you are
- Bachelor's degree in Computer Science, Engineering, Data Science, or a related field.
- Proven experience in AI/ML engineering or related fields, ideally within a SaaS or cloud-based environment.
- Proven experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, or Keras.
- Proven experience in a technical leadership or lead engineer role, demonstrating the ability to guide and mentor other engineers while maintaining significant individual contribution.
- Strong proficiency in Python (other languages such as R, Java, or C++ are a plus).
- Experience with cloud services like AWS, Azure, or Google Cloud Platform (GCP) for model deployment and scaling.
- Solid understanding of data structures, algorithms, and software engineering best practices.
- Expertise in model development, training, and evaluation (classification, regression, clustering, NLP, etc.).
- Strong background in data preprocessing, feature engineering, and time-series analysis.
- Experience with version control (Git) and agile development methodologies.
- Familiarity with MLOps practices, model versioning, and CI/CD pipelines for AI applications.
- Excellent problem-solving and debugging skills.
- Strong communication and teamwork skills, with the ability to explain complex technical concepts to non-technical stakeholders.
Perks & Culture
- Competitive salary and performance-based incentives.
- Dynamic and collaborative work environment.
- Grow & learn with a fast-growing organisation.
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