The Team: The Foreseer team delivers digital transformation solutions for information extraction from structures and semi structured documents and websites. Foreseer is a human in the loop platform that combines latest AI/ML advances with a state-of-the-art UI for delivering multiple projects, all powered by a core distributed, cloud native, auto scalable framework. Team comprises of experts in Java and Python language and ML engineers.

Job Brief

We are looking for a Machine Learning Engineer to help us improve our AI products and create new ML applications.

ML Engineer responsibilities include transforming data into useful features using machine learning techniques to feed predictive algorithms. To succeed in this role, you should possess outstanding skills in statistical analysis, machine learning methods and feature engineering techniques.

Your goal is to develop efficient self-learning AI applications.

Responsibilities

- Study and transform data science prototypes
- Design AI/ML applications
- Leverage large language models and vision language models for information retrieval
- Select appropriate annotated datasets for Supervised Learning methods
- Use effective feature engineering to transform raw data into useful features
- Find and implement the right algorithms and tools for ML tasks
- Develop ML systems according to requirements
- Train the developed model and run evaluation experiments
- Integrate the models in application flow and deploy at scale
- Perform statistical analysis of results and refine models




- Extend ML libraries and frameworks to apply in various ML tasks
- Remain updated in the rapidly changing field of machine learning

Requirements and Skills

- BS or MS degree in Computer Science, AI/ML, Data Science or related field.
- 9+ Years hands on experience in AI/ML, Data Science.
- Knowledge of Python and related libraries.
- Ability to effectively write robust and testable code and design software architecture.
- Understanding of ML techniques for feature engineering, data preprocessing, data structures and modelling.
- Strong understanding of AI technologies (e.g. Generative AI, NLP, Computer Vision) and their business applications.
- Hands on experience in leveraging language models for information retrieval.
- Deep understanding of feature engineering techniques, statistics and machine learning algorithms (such as regression, classification, clustering, neural networks, etc.)
- Familiarity with AI platforms (e.g., TensorFlow, PyTorch), libraries (like scikit-learn) and cloud AI services (AWS, GCP, Azure).
- Experience in different data base technologies (like RDBMS, NOSQL)
- Experience in Containerization, cloud platforms, CI/CD, and deployments through CI/CD pipelines, and AWS services like S3, EKS, EC2 etc.
- Proficiency in the development workplace, including IDE, web & application server, GIT, Azure DevOps, unit-testing tool and defect management tools
- Strong communication skills
- An analytical mind with problem-solving abilities

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